recentpopularlog in

jerryking : biases   90

« earlier  
The promise of synthetic data
February 4, 2020 | Financial Times | by Anjana Ahuja.

* Race after Technology by Ruha Benjamin.
Where anonymization fails, synthetic data might yet succeed. Synthetic data is artificially generated. It is most often created by funnelling real-world data through a noise-adding algorithm to construct a new data set. The resulting data set captures the statistical features of the original information without being a giveaway replica. Its usefulness hinges on a principle known as differential privacy: that anybody mining synthetic data could make the same statistical inferences as they would from the true data — without being able to identify individual contributions........Synthetic data has the potential to squeeze useful information from tightly-controlled databases. Uncovering fraud, for example, can be challenging because regulations restrict how information can be shared, even within banks. Synthetic data can help to unveil useful patterns, while masking individual incidents.......“If you’re trying to train an algorithm to detect fraud, you don’t care about specific transactions and who made them,” he says. “You care about the statistics, like whether the amounts are just below the limit needed to trigger an audit, or if they tend to occur close to the end of the quarter.” Those kinds of numbers can be shaken out of synthetic data as well as from the original........the UK’s Office for National Statistics says synthetic data offers a “safer, easier and faster way to share data between government, academia and the private sector”........ The data does not have to be rooted in the real world to have value: it can be fabricated and slotted in where some is missing or hard to get hold of........Synthetic data could, of course, be framed as fake data — but in some circumstances that is a bonus. Artificial intelligence that is trained on real-life information flaunts a baked-in bias: algorithmic decision-making in fields such as criminal justice and credit scoring shows evidence of racial discrimination........discrimination is not something that AI should perpetuate ..... synthetic data could help tackle complex social issues such as poverty: “We could modify that bias. People could release synthetic data that reflects the world we would like to have. Why not use those as training sets for AI?"
algorithms  anonymity  anonymized  biases  books  dark_side  data  data_wrangling  differential_privacy  fairness   inequality  noise  privacy  racial_discrimination  synthetic_data 
19 days ago by jerryking
Where Women Fall Behind at Work: The First Step Into Management - WSJ
Oct. 15, 2019 | WSJ | By Vanessa Fuhrmans.

Long before bumping into any glass ceiling, many women run into obstacles trying to grasp the very first rung of the management ladder—and not because they are pausing their careers to raise children—a new, five-year landmark study shows. As a result, it’s early in many women’s careers, not later, when they fall dramatically behind men in promotions, blowing open a gender gap that then widens every step up the chain...... fix that broken bottom rung of the corporate ladder, and companies could reach near-parity all the way up to their top leadership roles within a generation.....“Bias still gets in the way—bias of who you know, who’s like you, or who performs and operates the same way you perform and operate, whose style is more similar.....Employers’ moves to diversify their most senior echelons could provide a road map.....“We’ve seen that if companies really put their minds to it, they can bring about change that matters,” Ms. Thomas says. “If they can apply the same extra elbow grease that they do at the top to the broken rung.........The numbers show that the first step is the steepest for women. But why is that? What’s holding women back from climbing that first rung into management?

It isn’t for lack of ambition..... while many employers have increased their efforts to groom and elevate more senior women—a smaller, select group—fewer have applied the same rigor to cultivating more junior female managers....The upshot: At nearly every career stage, the disparities between men and women have narrowed only marginally since the Women in the Workplace research began in 2015. Even in industries with largely female entry-level workforces, such as retail and health care, men come to dominate the management ranks—a phenomenon that Haig Nalbantian, a labor economist and co-leader of consulting firm Mercer LLC’s Workforce Sciences Institute, calls “the flip.......even in many “female-friendly” sectors, entry-level women still tend to get hired into jobs with limited upward mobility, such as bank tellers or customer-service staff. ..“When companies ask, ‘What’s the one thing we can do systemically?’ we say, ‘It’s not quotas, it’s not targets,’” says Mr. Nalbantian. “It’s about how do you position women and minorities to succeed in the roles that are likely to lead to higher-level positions.”......The takeaway for some women is that they have to assemble their own career ladder.....To secure a sponsor, “you’ve got to consistently perform, have a strong brand and deliver. That’s just table stakes,” she says. “But a lot of people do that and might still not move, because they don’t have the right support.”
barriers_to_entry  biases  coaching  diversity  entry-level  female-friendly  glass_ceilings  gender_gap  management  movingonup  obstacles  sponsorships  takeaways  talent_pipelines  up-and-comers  women  workforce  workplaces 
october 2019 by jerryking
Productivity Without Privilege: How to Succeed When You’re Marginalized or Discriminated Against in the Workplace
Oct. 1, 2019 | The New York Times | By Alan Henry.

Productivity isn’t just about getting things done — it’s about spending less time on the things you have to do so you can spend more time on the things you want to do.....so much popular productivity advice is accessible only to people who have the option to use it in the first place (e.g. if your boss or co-workers believe that women shouldn’t be in the workplace, or that African-Americans are unmotivated, no “productivity hack” will force them to objectively look at your accomplishments and decisions the way they would employees they view without biases.)......the real factor determining whether you can take productivity advice at face value is "privilege".

* ‘Glamour work’ vs. ‘housework’: Who gets the opportunities matters.....

A 2018 story in Harvard Business Review pointed out that women of color in the workplace are asked to do “office housework” — the behind-the-scenes tasks that keep departments and teams humming — more often than white employees. That kind of work rarely raises an employee’s profile, in contrast to “glamour work,” which is highly visible, helps people make a name for themselves and leads to promotions and other career success.

* Trust your gut: Don’t get gaslit!!
Unfair treatment in the workplace often comes in the form of “microaggressions” — subtle actions that undermine a person and are often explained away by forgetfulness, ignorance, or anything but the malice that usually inspired them. ....gather proof — your own, or someone else’s — to remove doubt (e.g. collect the data — literally document the number of times you’ve been asked to do the office housework). Also, take note of the instances where colleagues are asked to do glamour work, and who they are......find colleagues you can speak with candidly. This way you have a sounding board to help you objectively see through your own self-doubt and determine whether you’ve actually been slighted or ignored, or whether you’re being paranoid.

* You don’t have to be twice as good, but you do have to “manage up”

If you're often volunteering for work that’s less glamorous — the office housework — to make a positive impact, or be seen as active and engaged..... while this drive is well meaning, it can often be counterproductive, and it gives managers cover to ignore their own behaviors and implicit biases when assigning work or handing out opportunities. Your best tool in this case, she said, is learning the fine art of saying "no" without ruining your career......learn how to “manage up” viz a viz your boss. Recognizing quickly whether something is a small or large ask, and how it fits into your personal or team priorities is essential — and asking your boss for clarity on what your team’s priorities are is also essential.

* Beware the lure of “just helping out”.
learning to, and practicing how to, hold back the urge to constantly volunteer,”

* Protect your boundaries.
when some people use methods like these (e.g. “check your email once or twice a day instead of being always available” and “leave your work at work,” ) to improve their work/life balance, they’re seen as organized and productive. When women and workers of color do the same, they can be viewed seen as unmotivated, lazy, or disengaged......call out bias when you experience it,” Ms. Tulshyan said. “Again, it only works in environments where you have the psychological safety — which, sadly, is rare for employees of color — but I’ve taken managers aside in the past and said, ‘I’ve noticed you volunteered me for this committee again, but not my white male colleagues. Could we talk about that?’” The same tactic works in reverse. If you notice that your privileged colleagues are the only ones sent to conferences or given the opportunity to discuss the work your team is doing, mention it to your manager.

* Document everything: Data is your best friend.
keep a work diary of accomplishments and challenges.....look for allies,” “I’ve had a few more-privileged colleagues at my workplaces who would spread the word to our department on my behalf if I accomplished something noteworthy. The great thing is it seems to foster a lot more trust and celebration among the group than if you are always tooting your own horn.”....if you feel frustrated and marginalized, try to keep in mind why you do the work you do, and remember the people who are positively affected by it.
biases  disrespect  equality_of_opportunity  glamour_work  gut_feelings  HBR  managing_up  marginalization  note_taking  office_housework  power_dynamics  privilege  productivity  protect_boundaries  record-keeping  say_"no"  self-doubt  sounding_boards  stereotypes  work_smarter  workplaces 
october 2019 by jerryking
The biggest gender divide is in mathematics
September 5, 2019 | | Financial Times| by Carola Hoyos.

Numeracy is vital for everyone. But according to Alain Dehaze, chief executive of Adecco, the world’s biggest recruiting company, the most valuable mathematical skills in a more automated future, especially for those people who can also communicate them to generalists, are the ability to spot patterns; to problem solve logically; and to work with statistics, probability and large data sets to see into the future.
biases  Communicating_&_Connecting  culture  gender_gap  generalists  girls  high_schools  massive_data_sets  mathematics  numeracy  parenting  pattern_recognition  probability  problem_solving  statistics  trend_spotting  women 
september 2019 by jerryking
Captaincy - Peggy Noonan's Blog - WSJ
Aug 4, 2014 |WSJ| Peggy Noonan

There are [underlying] reasons for [the existence of the weirdest] traditions and arrangements [--but you have to ask questions to uncover them]. Sometimes they are good and sometimes not, but they are reasons, explanations grounded in some sort of experience. I had a conversation about this a few years ago with a young senior at Harvard who on graduation would go to work for a great consulting firm that studies the internal systems of business clients to see if they can be bettered. He asked if I had any advice, which I did not. Then I popped out, with an amount of feeling that surprised me because I didn’t know I had been thinking about it, that he should probably approach clients with the knowledge that systems and ways of operating almost always exist for a reason. Maybe the reason is antiquated or not applicable to current circumstances, but there are reasons for structures, and if you can tease them out they will help you better construct variations or new approaches. I can’t remember why but this opened up a nice conversation about how consultants walk into new jobs with a bias toward change—the recommendation of change proves their worth and justifies their fees—but one should be aware of that bias and replace it with a bias for improvement, which is different.
Peggy_Noonan  traditions  advice  biases  bias_for_improvement  bias_toward_change  institutional_knowledge  internal_systems  Jason_Isaacs  management_consulting  institutional_memory 
april 2019 by jerryking
The robot-proof skills that give women an edge in the age of AI
February 11, 2019 | Financial Times |by Sarah O’Connor.

in a world of algorithms and artificial intelligence, communication skills and emotional intelligence — traditionally seen as female strengths — could prove key.

The latest panic about artificial intelligence is that it will deal a blow to women in the workplace..... The concerns are legitimate enough, but they fail to appreciate the big ways in which the world of work is going to change. In fact, it is quite possible the age of AI will belong to women. Men are the ones in danger of being left behind....Some AI tools may be biased against women — a risk for any group that has been historically under-represented in the workplace. Because machine learning tends to learn from historical data, it can perpetuate patterns from the past into the future......It is right to pay attention to these problems and work on solutions. Algorithms shouldn’t be given power without transparency, accountability, and human checks and balances. Top AI jobs should be held by a more diverse set of smart people.....As machines become better at many cognitive tasks, it is likely that the skills they are relatively bad at will become more valuable. This list includes creative problem-solving, empathy, negotiation and persuasion. As Andy Haldane, chief economist at the Bank of England, has put it, “the high-skill, high-pay jobs of the future may involve skills better measured by EQs (a measure of emotional intelligence) than IQs”..... increasing demand in these jobs for supplementary skills such as emotional intelligence, which has given women an edge.....as the AI era dawns, it is the right moment to overhaul the way we value these skills, and the way we teach them. With an eye on the demands of the future, we are trying to persuade girls that coding is not just for boys. So why aren’t we also trying to persuade boys that empathy is not just for girls?

We could start by changing the language we use. For too long we have talked about “soft skills”, with connotations of femininity and a lack of rigour. Let’s call them what they are: “robot-proof skills” that neither men nor women can afford to face the 21st century
21st._century  algorithms  artificial_intelligence  biases  checks_and_balances  dark_side  emotional_intelligence  EQ  future-proofing  gender_gap  machine_learning  soft_skills  smart_people  under-representation  women  workplaces  pay_attention  historical_data 
february 2019 by jerryking
Roger McNamee on how to tame Big Tech
February 7, 2019 | Financial Times | Roger McNamee.

Government intervention of this kind is a first step on the path to resolving the privacy issues that result from the architecture, business models and culture of internet platforms. But privacy is not the only problem we must confront. Internet platforms are transforming our economy and culture in unprecedented ways. We do not even have a vocabulary to describe this transformation, which complicates the challenge facing policymakers....Google, Facebook and other internet platforms use data to influence or manipulate users in ways that create economic value for the platform, but not necessarily for the users themselves. In the context of these platforms, users are not the customer. They are not even the product. They are more like fuel.....Google, Facebook and the rest now have economic power on the scale of early 20th-century monopolists such as Standard Oil. What is unprecedented is the political power that internet platforms have amassed — power that they exercise with no accountability or oversight, and seemingly without being aware of their responsibility to society......When capitalism functions properly, government sets and enforces the rules under which businesses and citizens must operate. Today, however, corpor­ations have usurped this role. Code and algorithms have replaced the legal system as the limiter on behaviour. Corporations such as Google and Facebook behave as if they are not accountable to anyone. Google’s seeming disdain for regulation by the EU and Facebook’s violations of the spirit of its agreement with the US FTC over user consent are cases in point......AI promises to be revolutionary. That said, it will not necessarily be a force for good. The problem is the people who create AI. They are human...McNamee recommends two areas of emphasis: regulation and innovation. As for the former, the most important requirement is to create and enforce standards that require new technology to serve the needs of those who use it and society as a whole. ...... The IoT requires our approval. Do not give it until vendors behave responsibly. Demand that policymakers take action to protect public health, democracy, privacy, innovation and the economy.
accountability  Alexa  antitrust  artificial_intelligence  biases  Big_Tech  consent  dark_side  Facebook  Google  Industrial_Internet  monopolies  personal_data  platforms  political_power  privacy  Roger_McNamee  sensors  surveillance  unintended_consequences 
february 2019 by jerryking
Amazon offers cautionary tale of AI-assisted hiring
January 23, 2019 | Financial Times | by Andrew Hill.

the task of working out how to get the right people on the bus has got harder since 2001 when Jim Collins first framed it, as it has become clearer — and more research has underlined — that diverse teams are better at innovation. For good reasons of equity and fairness, the quest for greater balance in business has focused on gender, race and background. But these are merely proxies for a more useful measure of difference that is much harder to assess, let alone hire for: cognitive diversity. Might this knotty problem be solved with the help of AI and machine learning? Ming is sceptical. As she points out, most problems with technology are not technology problems, but human problems. Since humans inevitably inherit cultural biases, it is impossible to build an “unbiased AI” for hiring. “You simply have to recognise that the biases exist and put in the effort to do more than those default systems point you towards,” she says...........What Amazon’s experience suggests is that instead of sending bots to crawl over candidates’ past achievements, companies should be exploring ways in which computers can help them to assess and develop the long term potential of the people they invite to board the bus. Recruiters should ask, in Ming’s words, “Who will [these prospective candidates] be three years from now when they’re at their peak productivity inside the company? And that might be a very different story than who will deliver peak productivity the moment they walk in the door.”
Amazon  artificial_intelligence  hiring  future-proofing  Jim_Collins  machine_learning  recruiting  teams  Vivienne_Ming  cautionary_tales  biases  diversity  intellectual_diversity  algorithms  questions  heterogeneity  the_right_people 
january 2019 by jerryking
Devah Pager, Who Documented Race Bias in Job Market, Dies at 46 - The New York Times
By Katharine Q. Seelye
Nov. 8, 2018

Devah Pager wrote in her book, “Marked: Race, Crime and Finding Work in an Era of Mass Incarceration.
PhDs  obituaries  professors  race  biases  racial_disparities  sociologists  racial_discrimination  joblessness  mass_incarceration 
november 2018 by jerryking
Why It’s So Hard to Put ‘Future You’ Ahead of ‘Present You’ - The New York Times
Sept. 10, 2018 | NYT | By Tim Herrera.

Are there instances when Past You has, quite inconsiderably, set up Future You for failure.

Why do we do this to ourselves? What makes us act against our own self-interest, even when we are acutely aware we’re doing so?....At work is present bias, our natural tendency to place our short-term needs and desires ahead of our long-term needs and desires. A lot of the time this comes in the form of procrastination.....we perceive our future selves the same way we perceive total strangers. In other words: When I’m brushing off responsibilities, part of my brain unconsciously believes that they’re now the problem of an actual stranger. ....starts with thinking of your future self as … you......Let’s say you habitually neglect your retirement savings. Instead of looking at future saving as making “financial decisions,” put yourself in the mind-set of thinking about the lifestyle you want when you’re retired. Picture yourself however many years hence, now retired, living the life you set up. Experts say this simple paradigm shift can change your entire approach to those decisions — even though they’re exactly the same.

Yes, this idea of future projection — “What will my life be like after I make this decision?” — is difficult to wrap your head around, especially when Future You is getting a better deal than Present You.
biases  present_bias  procrastination  retirement  self-interest  self-sabotage  short-term_thinking  visioning 
september 2018 by jerryking
‘Lopping,’ ‘Tips’ and the ‘Z-List’: Bias Lawsuit Explores Harvard’s Admissions Secrets
July 29, 2018 | - The New York Times | By Anemona Hartocollis, Amy Harmon and Mitch Smith.
=======================================
One tries very hard to assess the candidate’s potential. Is he or she a self-starter? How much help has he had? Has the candidate peaked? How will he or she react to not being head of the class?

Does he or she have the core values, confidence, perspective and flexibility to adapt and thrive? Not surprisingly, companies and others prefer applicants who have what a law firm where I later recruited called “a can-do attitude.”
===============================
........The case has been orchestrated by Edward Blum, a longtime crusader against affirmative action and voting rights laws, and it may yield him a fresh chance to get the issue before the Supreme Court. The court turned away his last major challenge to university admissions, Fisher v. University of Texas at Austin, in 2016.

[Read: How other Ivy League schools are coming to Harvard’s defense.]

The debate goes back to the civil rights movement of the 1950s and ’60s. The assassination of the Rev. Dr. Martin Luther King Jr. in 1968 was a turning point, pushing colleges to redouble their efforts to be more representative of American society.

But Asians were an overlooked minority despite a long history of discrimination. .......The plaintiffs say that the personal rating — which considers an applicant’s character and personality — is the most insidious of Harvard’s admissions metrics. They say that Asian-Americans are routinely described as industrious and intelligent, but unexceptional and indistinguishable — characterizations that recall painful stereotypes for many people of Asian descent. (The applicant who was the “proverbial picket fence” was Asian-American.).........Professor Khurana, the Harvard College dean, acknowledged that Harvard was not always perfect, but said it was trying to get its practices right.

“I have a great deal of humility knowing that some day history will judge us,” Professor Khurana said. “I think that’s why we are constantly asking ourselves this question: How can we do better? How could we be better? What are we missing? Where are our blind spots?”
admissions  affirmative_action  Asian-Americans  blind_spots  Colleges_&_Universities  discrimination  diversity  Harvard  Ivy_League  lawsuits  race-blind  race-conscious  selection_processes  biases  elitism  ethnic_stereotyping  meritocratic  students  racial_disparities  1968  core_values 
august 2018 by jerryking
Opinion | How James Brown Made Black Pride a Hit
July 20, 2018 | The New York Times | By Randall Kennedy, law professor at Harvard.

African-Americans have internalized society’s derogation/denigration of blackness....It was precisely because of widespread colorism that James Brown’s anthem “Say It Loud, I’m Black and I’m Proud” posed a challenge, felt so exhilarating, and resonated so powerfully....the song was written a half century go.....but, alas, the need to defend blackness against derision continues......Various musicians in the 1960s tapped into yearnings for black assertiveness, autonomy and solidarity. Curtis Mayfield and the Impressions sang “We’re a Winner.” Sly and the Family Stone offered “Stand.” Sam Cooke (and Aretha Franklin and Otis Redding) performed “A Change is Gonna Come.” But no entertainer equaled Brown’s vocalization of African-Americans’ newly triumphal sense of self-acceptance.

That Brown created the song most popularly associated with the Black is Beautiful movement is ironic.....At the very time that in “Say It Loud,” Brown seemed to be affirming Negritude, he also sported a “conk” — a distinctive hairdo that involved chemically removing kinkiness on the way to creating a bouffant of straightened hair. Many African-American political activists, especially those with a black nationalist orientation, decried the conk as an illustration of racial self-hatred....by 1968... prejudice against blackness remained prevalent, including among African-Americans.....Champions of African-American uplift in the 1960s sought to liberate blackness from the layers of contempt, fear, and hatred with which it had been smeared for centuries. Brown’s anthem poignantly reflected the psychic problem it sought to address: People secure in their status don’t feel compelled to trumpet their pride.....Colorism was part of the drama that starred Barack and Michelle Obama....Intra-racial colorism in Black America is often seen as a topic that should, if possible, be avoided, especially in “mixed company.” .....Colorism, however, remains a baleful reality.....
'60s  African-Americans  blackness  black_liberation_movement  black_nationalism  black_pride  Black_Is_Beautiful  colorism  James_Brown  music  Negritude  self-identification  songs  Spike_Lee  soul  white_supremacy  biases  self-acceptance  self-hatred  shadism  hits  1968 
july 2018 by jerryking
The Psychology of Money · Collaborative Fund
“Investing is not the study of finance. It’s the study of how people behave with money… It helps, I’ve found, when making money decisions to constantly remind yourself that the purpose of investing is to maximize returns, not minimize boredom. Boring is perfectly fine. Boring is good. If you want to frame this as a strategy, remind yourself: opportunity lives where others aren’t, and others tend to stay away from what’s boring.......few things in money are as valuable as options. The ability to do what you want, when you want, with who you want, and why you want, has infinite ROI.”

The finance industry talks too much about what to do, and not enough about what happens in your head when you try to do it.

This report describes 20 flaws, biases, and causes of bad behavior I’ve seen pop up often when people deal with money.
biases  personal_finance  psychology  boring  optionality  investing 
june 2018 by jerryking
Cry revolution if you like, Alexa is not listening
FEBRUARY 16, 2018 | FT | Henry Mance.

We know that a revolt against Big Tech is coming. All the ingredients are there: unaccountable elites, wealth disparities, popular discontent......We should be drawing the opposite lesson. We should be grateful for these moments when technology fails: they remind us that we are relying too much on algorithms.

Silicon Valley has created such gloriously useful products that we mostly overlook their limitations. We don’t notice that Google inevitably has a bias towards certain sources of information, or that Amazon directs us towards certain products. We forget that messaging apps draw us away from other forms of interaction. Already Snapchat has over 100m users who use it for more than 30 minutes a day on average. Already you can have Alexa listen attentively to everything you say at home, which is more than any member of your family will. 

Occasionally, however, we are confronted with the imperfections of technology. We are shown online ads for products we have already bought or for which we are biologically ineligible. We are invited to connect on LinkedIn with people we’ve never met, but who have the same name as our first line manager.....It is these moments which allow us to see that the emperor has no clothes. They demonstrate that the software is only as clever as the humans who have designed it. They remind us that the real revolutionary act is to switch off.
backlash  platforms  Snapchat  imperfections  algorithms  biases  limitations  Big_Tech 
february 2018 by jerryking
When algorithms reinforce inequality
FEBRUARY 9, 2018 | FT | Gillian Tett.

Virginia Eubanks, a political science professor in New York, undertakes academic research was focused on digital innovation and welfare claims. ......Last month, she published Automating Inequality, a book that explores how computers are changing the provision of welfare services in three US regions: Indiana, Los Angeles and Pittsburgh. It focuses on public sector services, rather than private healthcare insurance, but the message is the same: as institutions increasingly rely on predictive algorithms to make decisions, peculiar — and often unjust — outcomes are being produced. And while well-educated, middle-class people will often fight back, most poor or less educated people cannot; nor will they necessarily be aware of the hidden biases that penalise them....Eubanks concludes, is that digital innovation is reinforcing, rather than improving, inequality. ...What made the suffering doubly painful when the computer programs got it wrong was that the victims found it almost impossible to work out why the algorithms had gone against them, or to find a human caseworker to override the decision — and much of this could be attributed to a lack of resources....a similar pattern is described by the mathematician Cathy O’Neil in her book Weapons of Math Destruction. “Ill-conceived mathematical models now micromanage the economy, from advertising to prisons,” she writes. “They’re opaque, unquestioned and unaccountable and they ‘sort’, target or optimise millions of people . . . exacerbating inequality and hurting the poor.”...Is there any solution? O’Neil and Eubanks suggest that one option would be to require technologists to sign something equivalent to the Hippocratic oath, to “first do no harm”. A second — more costly — idea would be to force institutions using algorithms to hire plenty of human caseworkers to supplement the digital decision-making.

A third idea would be to ensure that the people who are creating and running the computer programs are forced to think about culture, in its broadest sense.....until now digital nerds at university have often had relatively little to do with social science nerds — and vice versa.

Computing has long been perceived to be a culture-free zone — this needs to change. But change will only occur when policymakers and voters understand the true scale of the problem. This is hard when we live in an era that likes to celebrate digitisation — and where the elites are usually shielded from the consequences of those algorithms.
Gillian_Tett  Cathy_O’Neil  algorithms  inequality  biases  books  dark_side  Pittsburgh  poverty  low-income 
february 2018 by jerryking
3 Ways to Improve Your Decision Making
Walter Frick
JANUARY 22, 2018

Rule #1: Be less certain.
Nobel-prize-winning psychologist Daniel Kahneman has said that overconfidence is the bias he’d eliminate first if he had a magic wand. It’s ubiquitous, particularly among men, the wealthy, and even experts. Overconfidence is not a universal phenomenon — it depends on factors including culture and personality — but the chances are good that you’re more confident about each step of the decision-making process than you ought to be.

So, the first rule of decision making is to just be less certain — about everything. Think choice A will lead to outcome B? It’s probably a bit less likely than you believe. Think outcome B is preferable to outcome C? You’re probably too confident about that as well.

Once you accept that you’re overconfident, you can revisit the logic of your decision. What else would you think about if you were less sure that A would cause B, or that B is preferable to C? Have you prepared for a dramatically different outcome than your expected one?

Rule #2: Ask “How often does that typically happen?”
....think about how long similar projects typically take....In general, research suggests, the best starting point for predictions ­— a key input into decision making — is to ask “How often does that typically happen?”
This rule, known as the base rate, comes up a lot in the research on prediction, but it might be helpful for the judgment side of decision making, too. If you think outcome B is preferable to outcome C, you might ask: How often has that historically been the case? ...The idea with both prediction and judgment is to get away from the “inside view,” where the specifics of the decision overwhelm your analysis. Instead, you want to take the “outside view,” where you start with similar cases before considering the specifics of your individual case.

Rule #3: Think probabilistically — and learn some basic probability.
The first two rules can be implemented right away; this one takes a bit of time. But it’s worth it. Research has shown that even relatively basic training in probability makes people better forecasters and helps them avoid certain cognitive biases....Improving your ability to think probabilistically will help you with the first two rules. You’ll be able to better express your uncertainty and to numerically think about “How often does this usually happen?” The three rules together are more powerful than any of them alone.

Even though these rules are all things you can start using relatively quickly, mastering them takes practice. In fact, after you use them for a little while, you may become overconfident about your ability to make decisions. Great decision makers don’t follow these rules only when facing a particularly difficult choice; they return to them all the time. They recognize that even seemingly easy decisions can be hard — and that they probably know less than they think
decision_making  pretense_of_knowledge  base_rates  probabilities  Daniel_Kahneman  overconfidence  biases  certainty 
january 2018 by jerryking
When biased data holds a potentially deadly flaw
SEPTEMBER 27, 2017 | FT | Madhumita Murgia.

Researchers at scientific journal Nature said findings from its own investigation on the diversity of these data sets “prompted warnings that a much broader range of populations should be investigated to avoid genomic medicine being of benefit merely to ‘a privileged few’ ”.

This insidious data prejudice made me curious about other unintended biases in the tech world. Several new consumer technologies — often conceived by, built by and tested overwhelmingly on Caucasian males — are flawed due to biases in their design.
massive_data_sets  biases  data  data_driven  unintended_consequences  racial_disparities  algorithms  value_judgements 
january 2018 by jerryking
How I Avoid Confirmation Bias When Investing
Nov 8, 2017 | - The Experts - WSJ | By Ted Jenkin.

(1) Examine all evidence with equal rigor. If you have been sitting on cash during the stock market’s run this year or have been conservative with your investments choices, you may be feeling that you’ve missed out on big returns. And this could lead you to jump into some investments simply because you believe that the market highs will continue (and they have, after all), not because they are the right choice for your portfolio. I can remember a few years back when I thought I missed out on the 3-D printing run when those stocks were blazing.

You need to try to avoid such tendencies to accept confirming evidence without question by looking for real empirical data and evidence–and examining the evidence on both sides with equal rigor. For instance, consider whether the U.S. market is a better bet than international right now. Or, how the GOP tax plan will impact the markets. Make sure you ask yourself the tough questions.

In my case, I forced myself to first consider the downsides to investing in the emerging 3-D printing industry or what consolidation might happen along the way–and the effects it could have on the stocks I was considering. In the end, I took a pass.

(2) Get someone to play devil’s advocate. It has happened to the best of us, no matter our education or background in investing. You are at a dinner party or having a conversation in the kitchen at work when you hear someone say, “I just made 100% profit buying ABC stock, and this thing is just taking off.” When we hear of opportunities to make money, our interest is undoubtedly piqued. And if you hear a tip from a person you trust and like, chances are you will become convinced that it is, of course, a good idea.

Do yourself a favor and find someone you trust just as much to play devil’s advocate and argue the opposite. Ask the person to build a counter-argument using questions such as: What is the strongest reason to do something else? The second strongest reason? The third? What is the worst-case scenario? And can you live with it, if it happens? Then, consider this position with an open mind.

For me, it was a former boss. At times, I would grow frustrated with him because on the surface he would never agree with me when I presented an idea. Over the years, however, I realized it wasn’t really him challenging me as much as it was him challenging me to challenge my own thought process so I could be a better decision maker. His sage advice has made me a better investor today.

(3) Be honest with yourself about your motives. Have you ever heard the saying, “If you can see John Brown through John Brown’s eyes, you can sell John Brown what John Brown buys?” I think it applies to the way I’ve looked at investments in the past–and the motives behind my decisions. We often don’t realize the power of our own motives–and we aren’t honest with ourselves about what they are.

For instance, when I’ve made money in a stock in the past, I’ve felt that those gains justify holding onto to the stock for the long term–even if the stock isn’t performing as well as it once did. So now, when I start doing research about that stock’s prospects, I need to make sure that I am really gathering information to help figure me out the right time to sell the stock. This will help me to determine whether any long-held desire to keep an investment is rooted in sound financial reasoning or is just based on pride or another emotion.

(4) Don’t ask leading questions. One of the biggest mistakes you can make as an investor is to ask questions that set you up to get the answer you want–not the answer you need.....if you find that your financial adviser always agrees with your investment ideas, it may be time to find a different adviser. Healthy and heated debates with my adviser have allowed me to make better personal and business decisions over the years.
personal_finance  investing  confirmation_bias  questions  financial_advisors  worst-case  devil’s_advocates  biases  self-delusions  motivations  hard_questions  counter-arguments  red_teams  open_mind 
november 2017 by jerryking
A Former CIA Executive’s Advice On How To Make Hard Decisions | The future of business
05.28.15 | Fast Company | BY STEPHANIE VOZZA.
A Former CIA Executive’s Advice On How To Make Hard Decisions
A five-step decision-making process from a man who spent 25 years making life-and-death decisions.
(1) Question
(2) Drivers
(3) Metrics
(4) Data
(5) What's Missing/Blind Spots

1. FIND THE REAL QUESTION
Questions are NOT self-evident, says Mudd. Focusing on better questions up front yields better answers later.
“Good questions are hard to come up with,” he says. Delay data gathering and the conclusions.... think about exactly what it is we want to know..... Start with what you’re trying to accomplish and work your way back, instead of moving forward and making conclusions. The right question provides a decision advantage to the person at the head of the table.

2. IDENTIFY YOUR “DRIVERS”
Break down complex questions into characteristics or “drivers.” This approach gives you a way to manage data.
For example, sort data on Al Qaeda into information baskets that included money, recruits, leadership, communications, training, and access to weapons. When information flows in, rather than adding it to one unmanageable pile, sorting through it periodically, and offering a recitation of what appears to be relevant from the most recent stuff you’ve seen, file each bit into one of your baskets. Limit your drivers to 10.

3. DECIDE ON YOUR METRICS
Identify the metrics you’ll use to measure how the problem and solution are evolving over time.
What are the right metrics?
What are the new information sources and metrics?
Compare your thought process to the training process of an Olympic sprinter who measures success in hundredths of a second. “If we don’t, the analysis we provide will suffer the same fate as a sprinter who thinks he’s great but has never owned a stopwatch: he enters an elite competition, and reality intervenes,” Metrics provide a “mind mirror”–a system for judging your decisions. It provides a foundation for coming back to the table and assessing the process for success.

4. COLLECT THE DATA
Once you’ve built the framework that will help you make the hard decision, it’s time to gather the data. Overcome data overload by plugging data into their driver categories and excising anything that doesn’t fit. “Too much data might provide a false sense of security, and it doesn’t necessarily lead to clearer analytic decision making,”

Avoud intuition. It’s dangerous. Aggressively question the validity of your data. Once you have your data sorted, give yourself a grade that represents your confidence in assessing your question.

5. LOOK FOR WHAT’S MISSING
Complex analysis isn’t easy. Assume that the process is flawed and check for gaps and errors. Three common stumbling blocks are:

Availability bias: The instinct to rely on what you know or what has been most recently in the news.
Halo effect: When you write off the negative characteristics because you’re mesmerized by the positive attributes.
Intuitive versus analytic methodologies: when you go with your gut. Relying on intuition is dangerous.

Mudd says making complex decisions is hard work. “It’s a lot of fun to be an expert who bases their ideas on history and not a lot of fun to be an analyst who must always be assessing potential scenarios,” he says. “Every time you go into a problem, and before you rip into data, ask yourself, ‘Am I sure where I’m heading?’”
asking_the_right_questions  availability_bias  biases  decision_making  false_sense_of_security  gut_feelings  halo_effects  hard_choices  intuition  intelligence_analysts  life-and-death  metrics  Philip_Mudd  problem_definition  organizing_data  problem_framing  sorting  thinking_backwards 
october 2017 by jerryking
Ray Dalio and the Market’s Pulse
Sept. 24, 2017 | WSJ | By Andy Kessler

Has Ray Dalio lost the pulse? The founder of the $160 billion hedge fund Bridgewater Associates is all over the place spouting his management philosophy of radical transparency. .....The investment whiz lives and manages by a set of principles that employees have to memorize. ..... “Most problems are potential improvements screaming at you.” Or this reworked cliché: “While most others seem to believe that pain is bad, I believe that pain is required to become stronger.”.....Bridgewater is losing money this year. Through July its flagship fund is down 3%, while the market is up more than 10%. ......The core of investing is quite simple: Determine what everyone else thinks, and then figure out in which direction they are wrong. That’s it. No one tells you what they think. You’ve got to feel it. .....It’s all about figuring out what is priced into a stock right now. That’s the pulse of the market, the collective mind meld aggregated into stock prices. I know from experience this is the hardest part of running a hedge fund. You can find the greatest story ever, but if everyone already knows it, there’s no money to be made..... the pulse changes with each government statistic, each daily ringing of cash registers and satellite images taken of parking lots. That’s why stocks trade every day. Real-world inputs and the drifting pulse drive the psychotic tick of the stock market tape. ....How do you find that pulse? .....

It’s best to survey your own people......Dalio doesn’t care about employees’ opinions or ideas; he just wants to take their pulse to figure out what the market already knows. Or as he puts it: “The biggest mistake most people make is to not see themselves and others objectively.”....Too much capital is often a burden. There are only so many good investment ideas out there, and it’s late in this cycle.....“Truth—more precisely, an accurate understanding of reality—is the essential foundation for any good outcomes.” Here’s a truth: If Bridgewater has lost its mojo, Mr. Dalio would be smart to manage a much smaller pot of money rather than torture his employees.
Andy_Kessler  Ray_Dalio  Bridgewater  hedge_funds  investors  investing  biases  pretense_of_knowledge  principles  transparency  market_sentiment 
september 2017 by jerryking
Mental bias leaves us unprepared for disaster
August 14, 2017 | Financial Times | Tim Harford.

Even if we could clearly see a crisis coming, would it have made a difference?

The 2004 storm, Hurricane Ivan, weakened and turned aside before striking New Orleans. The city was thus given almost a full year's warning of the gaps in its defences. The near miss led to much discussion but little action.

When Hurricane Katrina hit the city, evacuation proved as impractical and the Superdome as inadequate as had been expected. The levees broke in more than 50 places, and about 1,500 people died. New Orleans was gutted. It was an awful failure but surely not a failure of forecasting.

Robert Meyer and Howard Kunreuther in The Ostrich Paradox argue that it is common for institutions and ordinary citizens to make poor decisions in the face of foreseeable natural disasters, sometimes with tragic results.

There are many reasons for this, including corruption, perverse incentives or political expediency. But the authors focus on psychological explanations. They identify cognitive rules of thumb that normally work well but serve us poorly in preparing for extreme events.

One such mental shortcut is what the authors term the “amnesia bias”, a tendency to focus on recent experience (i.e. "disaster myopia" the human tendency to dismiss long-ago events as irrelevant, to believe This Time is Different and ignore what is not under one’s nose). We remember more distant catastrophes but we do not feel them viscerally. For example, many people bought flood insurance after watching the tragedy of Hurricane Katrina unfold, but within three years demand for flood insurance had fallen back to pre-Katrina levels.

We cut the same cognitive corners in finance. There are many historical examples of manias and panics but, while most of us know something about the great crash of 1929, or the tulip mania of 1637, those events have no emotional heft. Even the dotcom bubble of 1999-2001, which should at least have reminded everyone that financial markets do not always give sensible price signals, failed to make much impact on how regulators and market participants behaved. Six years was long enough for the lesson to lose its sting.

Another rule of thumb is “optimism bias”. We are often too optimistic, at least about our personal situation, even in the midst of a more generalized pessimism. In 1980, the psychologist Neil Weinstein published a study showing that people did not dwell on risks such as cancer or divorce. Yes, these things happen, Professor Weinstein’s subjects told him: they just won’t happen to me.

The same tendency was on display as Hurricane Sandy closed in on New Jersey in 2012. Robert Meyer found that residents of Atlantic City reckoned that the chance of being hit was more than 80 per cent. That was too gloomy: the National Hurricane Center put it at 32 per cent. Yet few people had plans to evacuate, and even those who had storm shutters often had no intention of installing them.

Surely even an optimist should have taken the precautions of installing the storm shutters? Why buy storm shutters if you do not erect them when a storm is coming? Messrs Meyer and Kunreuther point to “single action bias”: confronted with a worrying situation, taking one or two positive steps often feels enough. If you have already bought extra groceries and refuelled the family car, surely putting up cumbersome storm shutters is unnecessary?

Reading the psychological literature on heuristics and bias sometimes makes one feel too pessimistic. We do not always blunder. Individuals can make smart decisions, whether confronted with a hurricane or a retirement savings account. Financial markets do not often lose their minds. If they did, active investment managers might find it a little easier to outperform the tracker funds. Governments, too, can learn lessons and erect barriers against future trouble.

Still, because things often do work well, we forget. The old hands retire; bad memories lose their jolt; we grow cynical about false alarms. Yesterday’s prudence is today’s health-and-safety-gone-mad. Small wonder that, 10 years on, senior Federal Reserve official Stanley Fischer is having to warn against “extremely dangerous and extremely short-sighted” efforts to dismantle financial regulations. All of us, from time to time, prefer to stick our heads in the sand.
amnesia_bias  biases  books  complacency  disasters  disaster_myopia  dotcom  emotional_connections  evacuations  financial_markets  historical_amnesia  lessons_learned  manias  natural_calamities  optimism_bias  outperformance  overoptimism  panics  paradoxes  perverse_incentives  precaution  recency_bias  short-sightedness  single_action_bias  Tim_Harford  unforeseen  unprepared 
august 2017 by jerryking
A Beauty Product’s Ads Exclude the Black Women Who Use It - The New York Times
By TRESSIE McMILLAN COTTOM MAY 3, 2017

..................When black women bought SheaMoisture products, they were rejecting powerful stereotypes about black women’s hair as inherently unattractive. Unwittingly or not, SheaMoisture was part of a political project for black women, helping us resist harmful biases about our natural hair that circumscribe our choices and well-being.

But Sundial Brands, the black-owned company that runs SheaMoisture, has its own goals. In 2015, it company sold a minority stakee to Bain Capital to finance an expansion. At the time, Richelieu Dennis, the chief executive of Sundial, said SheaMoisture would be pursuing the “new general market,” which he described as a “consolidation of cultures, ethnicities and demographics aligned with commonalities, needs and lifestyles.”

To believe it is possible to diversify SheaMoisture beyond its black natural-hair customer base, one must believe that black beauty is desirable for non-black consumers. For that to be true, black women would have to be an ideal beauty type in the global market that Mr. Dennis was going after. Mr. Dennis had one problem: reality..........SheaMoisture could not sell a product meant to make black women look “whiter,” such as a chemical treatment to straighten hair, without changing its entire product line. But it could concede to the demands of capital by marketing its existing products to non-black women. SheaMoisture eventually apologized, acknowledging the insult many black women felt. By prominently featuring white women in what had become a political project, the company had signaled to black women that we could never be enough.

Beauty is never just about preference. It is about economics and power and exclusion. Brands like SheaMoisture rely on certain ideas of what is beautiful to make money.
biases  blackness  personal_grooming  personal_care_products  women  African-Americans  hair  beauty  colorism  shadism  brands 
may 2017 by jerryking
To Be a Genius, Think Like a 94-Year-Old - The New York Times
Pagan Kennedy APRIL 7, 2017

Pagan Kennedy is the author of “Inventology: How We Dream Up Things That Change the World”

it’s easy for us middle-aged folk to believe that the great imaginative leaps are behind us, and that innovation belongs to the kids.

On the contrary, there’s plenty of evidence to suggest that late blooming is no anomaly. A 2016 Information Technology and Innovation Foundation study found that inventors peak in their late 40s and tend to be highly productive in the last half of their careers. Similarly, professors at the Georgia Institute of Technology and Hitotsubashi University in Japan, who studied data about patent holders, found that, in the United States, the average inventor sends in his or her application to the patent office at age 47, and that the highest-value patents often come from the oldest inventors — those over the age of 55.....The more I talked to Dr. Goodenough, the more I wondered if his brilliance was directly tied to his age. After all, he has been thinking about energy problems longer than just about anyone else on the planet.....“I’m old enough to know you can’t close your mind to new ideas. You have to test out every possibility if you want something new.”

When I asked him about his late-life success, he said: “Some of us are turtles; we crawl and struggle along, and we haven’t maybe figured it out by the time we’re 30. But the turtles have to keep on walking.” This crawl through life can be advantageous, he pointed out, particularly if you meander around through different fields, picking up clues as you go along. .... The tapestry reminds him of the divine power that fuels his mind. “I’m grateful for the doors that have been opened to me in different periods of my life,” he said. He believes the glass battery was just another example of the happy accidents that have come his way: “At just the right moment, when I was looking for something, it walked in the door.”
physics  batteries  energy  creativity  biases  patents  midlife  genius  aging  late_bloomers 
april 2017 by jerryking
Oxford Diary
4 March / 5 March | Financial Times | Madhumita Murgia.

The goals is to build a conversation around change, to make technological change less scary, to make sure people don't feel left behind because of technology---do this within 26 hrs.....In the Cotswolds, too, senior British media executive tells me his own experience of working with YouTubers "was more like a one-night stand than a marriage". "We use each other for numbers and legitimacy, but the question is will they ever understand the subtler issues of traditional programming? Rules? Political correctness?.....A government adviser tells me that they are afraid that AI will change the relationship between state and citizen....Algorithms helping governments make important social decisions. Algorithms are a kind of black box and that government many not be able to explain its choices when questioned.
Google  future  conferences  change  handpicked  entrepreneur  ISIS  civil_servants  algorithms  YouTube  mass_media  digital_media  artificial_intelligence  biases  value_judgements  large_companies  print_journalism  technological_change  cultural_clash 
march 2017 by jerryking
The Struggle Inside The Wall Street Journal
FEB. 14, 2017 | The New York Times | David Leonhardt.

The Journal’s newsroom is embroiled in a fight over the paper’s direction.

Many staff members believe that the paper’s top editor, Gerard Baker, previously a feisty conservative commentator, is trying to Murdoch-ize the paper. “There is a systemic issue,” one reporter told me. The dissatisfaction went public last week, with stories in Politico and the Huffington Post. At a staff meeting on Monday, Baker dismissed the criticism as “fake news,” Joe Pompeo and Hadas Gold of Politico reported.

As a longtime reader, admirer and competitor of The Journal, I think the internal critics are right. You can see the news pages becoming more politicized. You can also see The Journal’s staff pushing back, through both great journalism (including exposes on the Trump administration) and quiet insubordination.....The Journal’s opinion pages, of course, have long been conservative. And they have their own tensions: An editor critical of Trump was recently fired, The Atlantic reported. But The Journal’s news pages, like those of The New York Times, The Washington Post and elsewhere, have aspired to objectivity.

One way to understand the fight is through the lens of Fox News. Its former leader, Roger Ailes, knew that the country had become more polarized and that many viewers didn’t want sober objectivity. He also knew that most reporters leaned left, and their beliefs sometimes seeped into coverage.
WSJ  newspapers  Rupert_Murdoch  financial_journalism  biases  WaPo  internal_politics 
february 2017 by jerryking
To Be a Great Investor, Worry More About Being Wrong Than Right - MoneyBeat - WSJ
By JASON ZWEIG
Dec 30, 2016

The stunning surprises of 2016 should have taught all of us that the unexpected will happen. To be a good investor, you have to be right much of the time. To be a great investor, you have to recognize how often you may be wrong. Great investors like Warren Buffett practice trying to disprove their investing assumptions to determine whether they are correct.

Techniques to combat these cognitive biases:

Shun peer pressure from social media or the Internet. If you reveal your opinion to a group that has strong views, the sociologist Robert K. Merton has warned, the ensuing debate becomes more “a battle for status” than “a search for truth.” Instead, get a second opinion from one or two people you know and can trust to tell you if they think you are wrong.

Listen for signals you might be off-base. Use Facebook or Twitter not as an amen corner of people who agree with you, but to find alternative viewpoints that could alert you when your strategies are going astray.

Write down your estimates of where the Dow Jones Industrial Average, oil, gold, inflation, interest rates and other key financial indicators will be at the end of 2017. If you don’t know, admit it. Ask your financial advisers to do the same. Next Dec. 31, none of you will be able to say “I knew that would happen” unless that’s what the record shows.

Book reference: Keith Stanovich, Richard West and Maggie Toplak point out in their new book, “The Rationality Quotient,” rational beliefs “must correspond to the way the world is,” not to the way you think the world ought to be.
==================================
Commenter:

What investors need to do is focus on their own investments, their strategies for each particular holding, long-term, income-oriented, speculative, etc. and stick to their plan without being distracted by peers and press looking for big headlines.
Warren_Buffett  biases  confirmation_bias  investors  books  Pablo_Picasso  personal_finance  investing  Jason_Zweig  pretense_of_knowledge  self-awareness  self-analysis  self-reflective  proclivities  warning_signs  signals  second_opinions  peer_pressure  DJIA  assumptions  mistakes  personal_economy  surprises  worrying 
january 2017 by jerryking
From Michael Lewis, a Portrait of the Men Who Shaped ‘Moneyball’ - The New York Times
By ALEXANDRA ALTERDEC. 3, 2016
Lewis decided to explore how it started.

The inquiry led him to the work of two Israeli psychologists, Amos Tversky and Daniel Kahneman, whose discoveries challenged long-held beliefs about human nature and the way the mind works.

Mr. Lewis chronicles their unusual partnership in his new book, “The Undoing Project,” a story about two unconventional thinkers who saw the world differently from everyone around them. Their peculiar area of research — how humans make decisions, often irrationally — has had profound implications for an array of fields, like professional sports, the military, medicine, politics, finance and public health.....Tversky and Kahneman's research demonstrating how people behave in fundamentally irrational ways when making decisions, relying on their gut rather than available data, gave rise to the field of behavioral economics. That discipline attracted Paul DePodesta, a Harvard student, who later went into sports management and helped upend professional baseball when he went to work for Mr. Beane.....Unlike many nonfiction writers, Mr. Lewis declines to take advances, which he calls “corrupting,” even though he could easily earn seven figures. Instead, he splits the profits from the books, as well as the advertising and production costs, with Norton. The setup spurs him to work harder and to make more money if the books are successful, he says.

“You should have the risk and you should enjoy the reward,” he said. “It’s not healthy for an author not to have the risk.”
Amos_Tversky  Michael_Lewis  Moneyball  books  book_reviews  unconventional_thinking  biases  cognitive_skills  unknowns  information_gaps  humility  pretense_of_knowledge  overconfidence  conventional_wisdom  overestimation  metacognition  behavioural_economics  irrationality  decision_making  nonfiction  writers  self-awareness  self-analysis  self-reflective  proclivities  Daniel_Kahneman  psychologists  delusions  self-delusions  skin_in_the_game  gut_feelings  risk-taking  partnerships 
december 2016 by jerryking
Fascination and Fear: Covering the Black Panthers - The New York Times
By GIOVANNI RUSSONELLO
OCT. 15, 2016“At the same time the newspaper was dubious and skeptical of them, it also gave them a tremendous amount of coverage,” said Jane Rhodes, a professor of African-American studies at the University of Illinois at Chicago, and the author of “Framing the Black Panthers: The Spectacular Rise of a Black Power Icon.”

“The media, like most of white America, was deeply frightened by their aggressive and assertive style of protest,” Professor Rhodes said. “And they were offended by it.”

When Huey P. Newton and Bobby Seale founded the Black Panther Party, their first goal was to confront what they saw as an epidemic of police brutality. They took to the streets with rifles, standing guard over policemen on patrol. The California Assembly responded quickly, proposing a law to ban the open carrying of firearms.....Looking at contemporary news coverage, Professor Rhodes said progress has been made when it comes to covering race and activism. “I see organizations like The Times making a much more sustained effort at deeper coverage,” she said. But articles still tend to emphasize the conflict between the police and protesters, she said, without addressing the core principles guiding social movements such as Black Lives Matter: greater investment in public education, community control of law enforcement and economic justice.
Black_Panthers  African-Americans  '60s  fear  FBI  public_opinion  NYT  newspapers  disinformation  biases  books  iconic  Black_Power 
october 2016 by jerryking
Algorithms Aren’t Biased, But the People Who Write Them May Be - WSJ
By JO CRAVEN MCGINTY
Oct. 14, 2016

A provocative new book called “Weapons of Math Destruction” has inspired some charged headlines. “Math Is Racist,” one asserts. “ Math Is Biased Against Women and the Poor,” declares another.

But author Cathy O’Neil’s message is more subtle: Math isn’t biased. People are biased.

Dr. O’Neil, who received her Ph.D in mathematics from Harvard, is a former Wall Street quant who quit after the housing crash, joined the Occupy Wall Street movement and now publishes the mathbabe blog.
algorithms  mathematics  biases  books  Cathy_O’Neil  Wall_Street  PhDs  quants  Occupy_Wall_Street  Harvard  value_judgements 
october 2016 by jerryking
A field guide to lies : critical thinking in the information age : Levitin, Daniel J., author. : Book, Regular Print Book : Toronto Public Library
Year/Format: 2016, Book , 304 pages

It's becoming harder to separate the wheat from the digital chaff. How do we distinguish misinformation, pseudo-facts, distortions and outright lies from reliable information? In A Field Guide to Lies, neuroscientist Daniel Levitin outlines the many pitfalls of the information age and provides the means to spot and avoid them. Levitin groups his field guide into two categories--statistical infomation and faulty arguments--ultimately showing how science is the bedrock of critical thinking. It is easy to lie with stats and graphs as few people "take the time to look under the hood and see how they work." And, just because there's a number on something, doesn't mean that the number was arrived at properly. Logic can help to evaluate whether or not a chain of reasoning is valid. And "infoliteracy" teaches us that not all sources of information are equal, and that biases can distort data. Faced with a world too eager to flood us with information, the best response is to be prepared. A Field Guide to Lies helps us avoid learning a lot of things that aren't true.
books  nonfiction  critical_thinking  infoliteracy  biases  lying  information_overload  TPL  Daniel_Levitin  engaged_citizenry  signals  noise  information_sources 
september 2016 by jerryking
The Problem With Slow Motion - The New York Times
By EUGENE M. CARUSO, ZACHARY C. BURNS and BENJAMIN A. CONVERSE AUG. 5, 2016
cognitive_skills  biases 
august 2016 by jerryking
Make Algorithms Accountable
AUG. 1, 2016 | The New York Times | By JULIA ANGWIN.

An algorithm is a procedure or set of instructions often used by a computer to solve a problem. Many algorithms are secret. ....Algorithms are ubiquitous in our lives. They map out the best route to our destination and help us find new music based on what we listen to now. But they are also being employed to inform fundamental decisions about our lives:
résumés sorting, credit scoring, prediction of a defendant’s future criminality.....as we rapidly enter the era of automated decision making, we should demand more than warning labels [about the algorithms that are being used].

A better goal would be to try to at least meet, if not exceed, the accountability standard set by a president not otherwise known for his commitment to transparency, Richard Nixon: the right to examine and challenge the data used to make algorithmic decisions about us.

Algorithms should come with warning labels. Obama White House called for automated decision-making tools to be tested for fairness, and for the development of “algorithmic auditing.”
tools  automation  decision_making  algorithms  data_driven  transparency  fairness  Richard_Nixon  proprietary  accountability  biases 
august 2016 by jerryking
How to have an ‘attitude of gratitude’
Jul. 19, 2016 | The Globe and Mail | BILL HOWATT Special to The Globe and Mail

gratitude = counting your good fortune -- such as having good health, feeling safe, having loving family and friends --and your well-being.

Your mental health is influenced by what you focus on -- if you focus on the positive, most likely you’ll feel more positive, too. The "98-2 theory" : It’s common for a person to report that 98% of their day is going well and 2% is not. Oftentimes, as a result, 98% of their focus is on the 2% that’s not going so well. This can then cloud their perceptions, and instill a negative bias, as to how well their life is going right now. It can also affect their level of stress and sense of balance and calm..... take a few moments each day to reflect and acknowledge what you have to be grateful for. This reflection can be done inside your head or in writing. This is called “an attitude of gratitude.”

Practicing gratefulness

Here are some simple ways you can start to practice gratefulness.

Awareness

For seven days, take a few moments at the end of each day to reflect and acknowledge what you are grateful for and why. Consider all the people with whom you interacted and the ones you thanked and acknowledged.

Get a daily boost

Gratitude can fuel life satisfaction and contentment. Through daily reflection and practice, gratitude can become a positive boost. When practiced regularly it can provide a positive reserve to draw upon in those moments of life when you feel stressed and challenged.

Evaluate daily

Once a day is over, you can’t get it back. You can, though, enjoy the journey. Taking time each day to focus on what you are grateful for is a discipline that takes practice.
gratitude  mindsets  biases  affirmations  negativity_bias 
july 2016 by jerryking
Eight steps to making better decisions as a manager - The Globe and Mail
HARVEY SCHACHTER
Special to The Globe and Mail
Published Sunday, May 08, 2016

Write down the key facts that need to be considered. Too often we jump into decisions and ignore the obvious.

Write down five pre-existing goals or priorities that will be affected by the decision.

Write down realistic alternatives – at least three, but ideally four or more.

Write down what’s missing. Information used to be scarce. Now it’s so abundant it can distract us from checking what’s missing (jk: i.e. the commoditization of information)

Write down the impact your decision will have one year in the future. By thinking a year out, you are separating yourself from the immediate moment, lessening emotions. [Reminiscent of Suzy Welch’s 10-10-10 rule. When you’re about to make a decision, ask yourself how you will feel about it 10 minutes from now? 10 months from now? and 10 years from now? People are overly biased by the immediate pain of some choice, but they can put the short-term pain in long-term perspective by asking these questions].

Involve at least two more people in the decision but no more than six additional team members. This ensures less bias, more perspectives, and since more people contributed to the decision, increased buy-in when implementing it.

Write down what was decided, as well as why and how much the team supports the decision.

Schedule a follow-up in one to two months.
Harvey_Schachter  decision_making  goals  buy-in  options  unknowns  following_up  note_taking  dissension  perspectives  biases  information_gaps  long-term  dispassion  alternatives  think_threes  unsentimental  Suzy_Welch  commoditization_of_information  process-orientation 
may 2016 by jerryking
The Choice Explosion - The New York Times
David Brooks MAY 3, 2016

Americans have always put great emphasis on individual choice. But even by our own standards we’ve had a choice explosion over the past 30 years.....making decisions well is incredibly difficult....It’s becoming incredibly important to learn to decide well, to develop the techniques of self-distancing to counteract the flaws in our own mental machinery....assume positive intent (i.e. when in the midst of some conflict, start with the belief that others are well intentioned).....People are overly biased by the immediate pain of some choice, but they can put the short-term pain in long-term perspective by asking these questions [Suzy Welch’s 10-10-10 rule. When you’re about to make a decision, ask yourself how you will feel about it 10 minutes from now? 10 months from now? and 10 years from now?]....make deliberate mistakes....our tendency to narrow-frame, to see every decision as a binary “whether or not” alternative. Whenever you find yourself asking “whether or not,” it’s best to step back and ask, “How can I widen my options?” In other words, before you ask, “Should I fire this person?” Ask, “Is there any way I can shift this employee’s role to take advantage of his strengths and avoid his weaknesses?”....It’s important to offer opportunity and incentives. But we also need lessons in self-awareness — on exactly how our decision-making tool is fundamentally flawed, and on mental frameworks we can adopt to avoid messing up even more than we do.
David_Brooks  choices  decision_making  biases  thinking_deliberatively  scarcity  self-awareness  metacognition  binary_decisionmaking  abundance  optionality  narrow-framing  Suzy_Welch  wide-framing  self-distancing 
may 2016 by jerryking
The Next Mark Zuckerberg Is Not Who You Might Think - The New York Times
JULY 2, 2015
Advertisement

Continue reading the main story
Claire Cain Miller
entrepreneur  biases  start_ups  venture_capital 
july 2015 by jerryking
Harvard Accused of Bias Against Asian-Americans
A complaint Friday alleged that Harvard University discriminates against Asian-American applicants by setting a higher bar for admissions than that faced by other groups. The complaint, filed by a…
Harvard  Colleges_&_Universities  admissions  Asian-Americans  biases  elitism  achievement_gaps  ethnic_stereotyping  meritocratic  students  racial_disparities  Ivy_League 
may 2015 by jerryking
The Measuring Sticks of Racial Bias - NYTimes.com
JAN. 3, 2015
Continue reading the main story
Economic View
By SENDHIL MULLAINATHAN
racial_disparities  racism  biases  African-Americans  race  Ferguson  résumés  bigotry  discrimination 
january 2015 by jerryking
Venture capital’s vicious circle - The Globe and Mail
Leah Eichler

Special to The Globe and Mail

Published Friday, Nov. 07 2014
venture_capital  gender_gap  biases  start_ups 
november 2014 by jerryking
Captaincy
There are reasons for traditions and arrangements. Sometimes they are good and sometimes not, but they are reasons, explanations grounded in some sort of experience. I had a conversation about this a ...
advice  biases  bias_for_improvement  bias_toward_change  institutional_knowledge  internal_systems  Jason_Isaacs  management_consulting  Peggy_Noonan 
november 2014 by jerryking
Five questions to hone your business strategy - The Globe and Mail
HARVEY SCHACHTER
Special to The Globe and Mail
Published Sunday, Sep. 28 2014

1. Why does our business deserve to succeed?
2. What would a new CEO do?
3. Imagine it is three to six years in the future and the proposed strategy has been unsuccessful. Why did it fail?
4. What would have to be true for our strategy to succeed?
5. Would I put my own money into this?
strategy  business_planning  Harvey_Schachter  execution  effectiveness  assumptions  anticipating  questions  biases  overconfidence  self-delusions  skin_in_the_game 
september 2014 by jerryking
The Mental Virtues - NYTimes.com
AUG. 28, 2014| NYT | David Brooks.

Thinking well under a barrage of information may be a different sort of moral challenge than fighting well under a hail of bullets, but it’s a character challenge nonetheless. In their 2007 book, “Intellectual Virtues,” Robert C. Roberts of Baylor University and W. Jay Wood of Wheaton College list some of the cerebral virtues. We can all grade ourselves on how good we are at each of them.

First, there is love of learning.
Second, there is courage. Not just the willingness to hold unpopular views. But the subtler form, which is knowing how much risk to take in jumping to conclusions. Reckless thinkers take scraps of information and leaps to some faraway conspiracy theories. Perfectionists are silenced, except under ideal conditions, for fear of being wrong. Intellectual courage is self-regulation--knowing when to be daring and when to be cautious. And guarding against confirmation bias.

Third, there is firmness. Don’t be the person who surrenders his beliefs at the slightest whiff of opposition. On the other hand, you don’t want to hold dogmatically to a belief against all evidence. The median point between flaccidity and rigidity is the virtue of firmness.

Fourth, there is humility, which is not letting your own desire for status get in the way of accuracy. Fight against vanity and self-importance.

Fifth, there is autonomy. Don’t be a person who slavishly adopts whatever opinion your teacher or some author gives you. On the other hand, don’t reject all guidance from people who know what they are talking about. Autonomy is the median of knowing when to bow to authority and when not to, when to follow a role model and when not to, when to adhere to tradition and when not to.[In this case, autonomy sounds a lot like judgment]

Finally, there is generosity. This virtue starts with the willingness to share knowledge and give others credit. But it also means hearing others as they would like to be heard, looking for what each person has to teach and not looking to triumphantly pounce upon their errors.
David_Brooks  thinking  howto  cognitive_skills  biases  virtues  humility  intellectual_courage  courage  autonomy  resolve  generosity  praise  grace  firmness  confirmation_bias  self-regulation  recklessness  cerebral  perfection  independent_viewpoints  discernment  self-importance  pairs 
august 2014 by jerryking
James Surowiecki: The Startup Mass Extinction : The New Yorker
BY JAMES SUROWIECKI
MAY 19, 2014

"Starting a company may be easier, but making it a success isn’t. Competition is fierce, profits are scarce, and venture capitalists aren’t generous when it comes to later stages of funding. As Gideon Lewis-Kraus shows in “No Exit,” a new Kindle Single about startup culture, the life of a new company is often brutish and short. Though we may be seeing a “Cambrian explosion” of new companies, as The Economist recently put it, there’s a mass extinction going on, too.

The fact that most new businesses fail is hardly a secret. So why are so many people gambling on ventures that are likely to end badly?
start_ups  biases  overconfidence  failure  James_Surowiecki  new_businesses  Cambrian_explosion 
june 2014 by jerryking
Bill Gates is naive, data is not objective | mathbabe
January 29, 2013 Cathy O'Neil,

Don’t be fooled by the mathematical imprimatur: behind every model and every data set is a political process that chose that data and built that model and defined success for that model.
billgates  naivete  data  Cathy_O’Neil  value_judgements  datasets  biases 
december 2013 by jerryking
Five mental mistakes that sabotage investors
Oct. 11 2013 | The Globe and Mail | John Heinzl.

Trying to break even

You buy a stock for $50 and it falls to $45 – and stays there. “I’ll just wait until it gets back to $50 and then I’ll sell it,” you tell yourself. The technical term for this behaviour is “anchoring,” and it’s a problem because the psychological desire to break even could cause you to hang on when there may be better opportunities elsewhere. What you paid for the stock is actually irrelevant; the only thing that matters now are the future prospects for the investment. If the outlook is lousy, you might be better off taking your lumps and moving on. If you still like the company’s prospects, then holding on may indeed make sense.

Focusing on your cost base

This is a closely related concept. You buy a stock for $50, and it rises to $60. Because you have an unrealized capital gain or “cushion” of $10, you feel good about holding on to the stock because a lot has to go wrong before you lose all of your paper profit. But as with the first example, the original price you paid for the stock is irrelevant. It’s history. What matters is where the stock goes from its current price of $60, not whether it stays above your original purchase price.

Recency bias

This is one of the most common traps. You see a stock chart that goes straight up, and you assume the stock will keep rising. Conversely, you see a chart that goes down and assume the losses will continue. Humans are wired to expect things that happened in the past to happen again, but investing is not that simple. In fact, mutual fund studies indicate that many investors underperform the market because they tend to buy near the top and sell near the bottom in the mistaken belief that the recent trend will continue, which it often doesn’t.

Mental accounting

Some investors compartmentalize their money based on its source or its purpose. ...When we use mental accounting, we ignore the fact that a dollar is a dollar; where the money came from shouldn’t influence how we spend it.

Refusing to put dividend stocks inside an RRSP
biases  personal_finance  investors  mistakes  recency_bias  anchoring  psychology  human_errors 
october 2013 by jerryking
Overcoming Your Negativity Bias - NYTimes.com
June 14, 2013, 12:44 pm Comment
Overcoming Your Negativity Bias
By TONY SCHWARTZ
Negative thoughts destroy one's concentration....write down everything you feel grateful for in that moment. you'll feel remarkably better, but also far more able to concentrate on the task at hand. .. If you’re a manager or a leader, you carry an extra responsibility. By virtue of your authority, your emotions are disproportionately influential. When you’re feeling worried, frustrated or angry, the people around you are going to pick it up – not least because they’ll be wondering whether they’re the cause. Is there someone on your team who is especially triggering you lately? Take a moment to think about the quality you most appreciate in that person – to remember what it was that drew you to that person in the first place.

Here’s the paradox: The more you’re able to move your attention to what makes you feel good, the more capacity you’ll have to manage whatever was making you feel bad in the first place. Emotions are contagious, for better or worse. It’s your choice.
cognitive_skills  biases  howto  self-criticism  gratitude  emotional_mastery  affirmations  self-defeating  self-doubt  negativity_bias  positive_thinking  pessimism 
june 2013 by jerryking
Is this a bias I see before me? - The Globe and Mail
LYSIANE GAGNON

From Monday's Globe and Mail

Published Monday, Jul. 31 2006,
Lebanon  biases  Hezbollah  human_rights  anti-Israel  anti-Semitism 
march 2013 by jerryking
For ‘House of Cards,’ Using Big Data to Guarantee Its Popularity - NYTimes.com
February 24, 2013 | NYT | By DAVID CARR

Rick Smolan wrote “The Human Face of Big Data.” “
Netflix, which has 27 million subscribers in the nation and 33 million worldwide, ran the numbers. It already knew that a healthy share had streamed the work of Mr. Fincher, the director of “The Social Network,” from beginning to end. And films featuring Mr. Spacey had always done well, as had the British version of “House of Cards.” With those three circles of interest, Netflix was able to find a Venn diagram intersection that suggested that buying the series would be a very good bet on original programming.

Big bets are now being informed by Big Data, and no one knows more about audiences than Netflix....But there are contrarian opinions, "“Data can only tell you what people have liked before, not what they don’t know they are going to like in the future,” he said. “A good high-end programmer’s job is to find the white spaces in our collective psyche that aren’t filled by an existing television show,” adding, those choices were made “in a black box that data can never penetrate.” "...The rise of the quants has some worried about the impact on quality and diversity of programming. Writing in Salon, Andrew Leonard wonders “how a reliance on Big Data might funnel craftsmanship in particular directions. What happens when directors approach the editing room armed with the knowledge that a certain subset of subscribers are opposed to jump cuts or get off on gruesome torture scenes” or are just interested in sexual romps?

Netflix insists that actual creative decisions will remain in the hands of the creators. “We don’t get super-involved on the creative side,” Mr. Evers said. “We hire the right people and give the freedom and budget to do good work.” That means that when Seth Rogen and Kristen Wiig are announced as special guests on coming episodes of “Arrested Development,” it is not because a statistical analysis told Netflix to do so.

But there are potential conflicts. Given that Netflix is in the business of recommending shows or movies, might its algorithms tilt in favor of the work it commissions as it goes deeper into original programming? It brings to mind how Google got crossed up when it began developing more products, and those began showing up in searches.

And there are concerns that the same thing that makes Netflix so valuable — it knows everything about us — could create problems if it is not careful with our data and our privacy.
David_Carr  Netflix  data_driven  massive_data_sets  streaming  data  television  digital_humanities  Asha_Isaacs  quantitative  big_bets  white_spaces  original_programming  human_psyche  craftsmanship  Venn_diagrams  content_creators  algorithms  biases  the_right_people 
february 2013 by jerryking
The Philosophy of Data - NYTimes.com
By DAVID BROOKS
Published: February 4, 2013

Big Data carries with it carry with certain cultural assumptions — that everything that can be measured should be measured; that data is a transparent and reliable lens that allows us to filter out emotionalism and ideology; that data will help us do remarkable things — like foretell the future....some of the questions raised by the data revolution: In what situations should we rely on intuitive pattern recognition and in which situations should we ignore intuition and follow the data? What kinds of events are predictable using statistical analysis and what sorts of events are not? Two things data does really well are:
(1) expose when our intuitive view of reality is wrong.
(2) data can illuminate patterns of behavior we haven’t yet noticed.
cultural_assumptions  David_Brooks  massive_data_sets  data  critical_thinking  pattern_recognition  intuition  biases  measurements  assumptions 
february 2013 by jerryking
Analytic Thinking and Presentation for Intelligence Producers.
The importance of a title
How to gist your reading (actually a very helpful section)
The need for focus and clarity
“If you can’t summarize your bottom line in one sentence, you haven’t done your analysis.”
One idea – One Paragraph
The inverted Pyramid writing style, i.e. begin with the core assumption.
The importance of precise language (no jargon, no abbreviations, allow no possible misunderstandings)
Again, there is nothing earth shattering, but it is an interesting read.
DEVELOPING ANALYTICAL OBJECTIVITY
The part that I found most interesting is the section entitled “Developing Analytical Objectivity.”
In a world filled with talk radio and infotainment, it is an important point to raise awareness about.
We have talked extensively about the cognitive nature of our brains and some of the fallacies and tricks our brains play on us – especially in the political arena.
This warning given to some of our country’s brightest thinkers acts as a reminder that if the smartest person in the room must protect against biases, so must we.
focus  clarity  strategic_thinking  critical_thinking  security_&_intelligence  writing  presentations  howto  sense-making  objectivity  biases  Philip_Mudd  analysts  misunderstandings  intelligence_analysts 
october 2012 by jerryking
Ride to the rescue of workers
Aug. 15 2007 | The Globe and Mail | JIM STANFORD. Economist with the Canadian Auto Workers Union

So imagine how surprised I was at the bank's rapid, powerful interventions into financial markets recently, issuing more than $4-billion in new low-cost loans in just three trading days to soothe frazzled nerves and keep the easy-credit machine out of the ditch. And it signalled in no uncertain terms there was plenty more where that came from.

Far from sitting back watching the economy "adjust to change," this drama featured the central bank as cavalry - charging over the hill just as the hedge-fund artists were making their last stand. Seems the prospect of bankrupt speculators tossed onto the street, forced to find real work, isn't the kind of change the bank has in mind. Now, don't get me wrong: What the bank did was prudent and important....This selective, one-sided approach to stabilization speaks volumes about the nature of the bank as an institution, and the biases of the inflation-targeting regime it espouses so passionately. The Bank of Canada is not a neutral, prescient team of technocrats, guiding us to some imaginary point of maximum efficiency. Like any other political body, its opinions and actions reflect value judgments about the relative importance of differing, sometimes conflicting, goals and interests. Job creation versus inflation control. Consumer inflation versus stock-market inflation. Financial troubles versus industrial troubles.

So, Governor Dodge, please carry on with your dramatic rescue mission. Just spread a little of that rescue around to the rest of us next time.
bailouts  Bank_of_Canada  biases  bubbles  business-government_relations  CAW  central_banks  economists  financial_crises  financial_markets  institutions  Jim_Stanford  layoffs  manufacturers  pairs  politics  tradeoffs  values  value_judgements 
june 2012 by jerryking
Investing Ideas That Stand Test of Time
April 25, 2000 | WSJ | Jonathan Clements

These days I find I am left with just three core investment ideas:
(1) Financial Success is a Sense of Control
If you ask folks about their financial goals, they will likely offer a laundry list of goods they want to buy or announce they want to accumulate as much money as possible. But in reality,
both goals are a prescription for unhappiness.
Sure it might be nice to purchase everything that catches your fancy. But nobody has unlimited wealth, so a focus on endless consumption inevitably results not in happiness, but in frustration and financial stress. Yeah, it would also be great to have heaps of money. But if all you want is an even bigger pile of cash, you will never be satisfied, because you will never reach your goal. So what should you
shoot for? A far more worthy goal, I believe, is eliminating the anxiety that comes with managing money. You want to reach that sweet spot where you feel your finances are under control, no matter what your standard of living and level of wealth.

(2)Investing is Simple
No doubts about it, there are lots of investments and investment strategies that are mighty complicated. But complexity usually means investors are running the risk of rotten results and Wall Street is getting the chance to charge fat fees. Investing is best when it is simple. In fact, if you want to accumulate a healthy nest egg, there
isn’t much to it. First, you have to save a goodly amount, preferably at least ten percent of your pre-tax annual income. Second, you should consider investing at least half of your portfolio in stocks, even if you are approaching retirement. Third, you should diversify broadly, owning a decent mix of large, small and foreign stocks. Fourth, you should hold down investment costs, including
brokerage commissions, annual fund expenses and taxes. Finally, you should give it time. A little humility also helps. Don’t waste effort — and risk havoc — by trying to pick the next hot stock, identify the next superstar fund manager or guess the market’s next move. Instead, your best bet is to buy and hold a few well-run mutual funds.

(3) We are the enemy
If successful investing is so simple, why do so many people mess up? It isn’t the markets that are the problem, it is the investors.
We make all sorts of mistakes. We fret about the performance of each investment that we own, so we don’t enjoy the benefits of diversification. We are often overly self-confident, which
prompts us to trade too much and bet too heavily on a single stock or market sector. We
extrapolate recent results, leading to excessive exuberance when stocks are rising and unjustified
pessimism when markets decline. We lack self-control, so we don’t save enough.

[All the points made immediately above are analogous to Jason Zweig's article on personal finance & investing. From Benjamin Graham --investing is often portrayed as a battle between you and the markets. Instead, “the investor’s chief problem — and even his worst enemy — is likely to be himself.”

Similarly, Nobel Laureate Daniel Kahneman wrote in his book Thinking, Fast and Slow. [that]evaluating yourself honestly is at least as important as evaluating your investments accurately. If you don’t force yourself to learn your limits as an investor, then it doesn’t matter how much you learn about the markets: Your emotions will be your undoing.... ]

If you are going to truly be a successful and happy investor, it isn’t enough simply to devise
strategies that allow you to meet your investment goals. Your strategies also must give you a
sense of financial control and fit with your risk tolerance, so that you stick with them through the
inevitable market turmoil.
That may mean keeping more of your money in bonds and money-market funds. It could mean
paying for an investment advisor. It might mean scaling back your financial goals and accepting
that the kids won’t be heading to Harvard and that you won’t be able to retire early.
These sorts of choices aren’t foolish. What’s foolish is settling on investment strategies without
considering whether you can see them through.
personal_finance  investing  howto  ideas  goal-setting  Nobel_Prizes  money_management  Jonathan_Clements  financial_literacy  biases  humility  mistakes  self-awareness  self-control  proclivities  overconfidence  financial_planning  delusions  self-delusions  emotions  human_frailties  Jason_Zweig  extrapolations  risk-tolerance  recency  unhappiness  human_errors  bear_markets  sense_of_control  superstars  Daniel_Kahneman 
may 2012 by jerryking
The 6 Habits of True Strategic Thinkers
Mar 20, 2012 | | Inc.com | Paul J. H. Schoemaker.
Adaptive strategic leaders--the kind who thrive in today’s uncertain environment--do six things well:

1. Anticipate. Hone your “peripheral vision.” Reduce vulnerabilities to rivals who detect and act on ambiguous signals. ... Build wide external networks to help you scan the horizon better
2. Think Critically. Critical thinkers question everything. To master this skill, you must force yourself to reframe problems to get to the bottom of things, in terms of root causes. Challenge current beliefs and mindsets, including your own Uncover hypocrisy, manipulation, and bias in organizational decisions.
3. Interpret. Ambiguity is unsettling. Faced with it, you are tempted to reach for a fast (potentially wrongheaded) solution. A good strategic leader holds steady, synthesizing information from many sources before developing a viewpoint. To get good at this, you have to:Seek patterns in multiple sources of data; Question prevailing assumptions and test multiple hypotheses simultaneously.
4. Decide. Many leaders fall prey to “analysis paralysis.” Develop processes and enforce them, so that you arrive at a “good enough” position. To do that well, you have to: Carefully frame the decision to get to the crux of the matter, Balance speed, rigor, quality, and agility. Leave perfection to higher powers. Take a stand even with incomplete information and amid diverse views
5. Align. Consensus is rare. Foster open dialogue, build trust, and engage key stakeholders, especially when views diverge. To pull that off, you need to: Understand what drives other people's agendas, including what remains hidden. Bring tough issues to the surface, even when it's uncomfortable
Assess risk tolerance and follow through to build the necessary support
6. Learn.

As your company grows, honest feedback is harder and harder to come by. You have to do what you can to keep it coming.
Encourage and exemplify honest, rigorous debriefs to extract lessons
Shift course quickly if you realize you're off track
Celebrate both successes and (well-intentioned) failures that provide insight
Do you have what it takes?
tips  leadership  habits  strategic_thinking  anticipating  critical_thinking  networks  biases  conventional_wisdom  decision_making  empathy  feedback  thinking  failure  lessons_learned  leaders  interpretation  ambiguities  root_cause  insights  paralyze  peripheral_vision  analysis_paralysis  reframing  course_correction  vulnerabilities  good_enough  debriefs  post-mortems  problem_framing  discomforts  wide-framing  outward_looking  assumptions  game_changers 
march 2012 by jerryking
The Recency Bias and How it Fools our Money Brains - NYTimes.com
February 13, 2012, 12:23 pm
Tomorrow’s Market Probably Won’t Look Anything Like Today
By CARL RICHARDS
cognitive_skills  biases  financial_planning  recency_bias 
february 2012 by jerryking
globeadvisor.com: Living in the real world of finance
December 9, 2011 | G&M | by David Parkinson.
Both a scientist and financial guru, Emanuel Derman warns of relying on mathematical models to predict stock movements. As David Parkinson reports, investors should beware the wild card of human nature...Mr. Derman was in Toronto discussing his new book, Models. Behaving. Badly: Why Confusing Illusion With Reality Can Lead to Disaster, on Wall Street and in Life.

DAVID PARKINSON
boundary_conditions  finance  quantitative  Wall_Street  Colleges_&_Universities  books  physics  models  mathematics  stockmarkets  biases  modelling  dangers  false_confidence  human_factor  stock_picking  illusions  oversimplification  in_the_real_world 
january 2012 by jerryking
Hiring Wrong—And Right
JANUARY 29, 2007| BusinessWeek |By Jack and Suzy Welch

the best way to handle hiring mistakes is to not hire them in the first place. Yes, bringing in the right people is, as noted above, a tough business fraught with pitfalls. But you can really improve your chances if you fight like hell against the three main hiring impulses that most often get managers into trouble.

The first is using your gut. Don't! When you have a big, crucial job opening to fill, it's just too easy to fall in love with a shiny new candidate who is on his best behavior, telling you exactly what you want to hear and looking like the answer to all your prayers. That's why you can never hire alone. Make sure a team coolly analyzes the candidate's credentials and conducts interviews. And by all means, make sure the team includes at least one real hard-nose—the kind of naysayer who is particularly good at sussing out the job fit and sniffing out the phonies.

The second instinct you have to fight is what we call the "recommendation reflex," in which managers rationalize away negative references with excuses like: "Well, our job is different." You should seek out your own references to call, not just the ones provided by the candidate, and force yourself to listen to what they have to tell you even if it ruins the pretty picture you are painting in your head.

Finally, fight the impulse to do all the talking. Yes, you want to sell your job, but not at all costs. In interviews, ask candidates about their last job—and then shut up for a good, long while. As they describe what they liked and what they didn't, you will likely hear much of what you really need to know about fit.

True, you may still make a mistake, but at least it won't be because you rushed. Save the speed for fixing things if they unfortunately go awry.
Jack_Welch  hiring  intuition  mistakes  decision_making  Octothorpe_Software  biases  impulse_control  gut_feelings  the_right_people 
october 2011 by jerryking
« earlier      
per page:    204080120160

Copy this bookmark:





to read