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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
What Land Will Be Underwater in 20 Years? Figuring It Out Could Be Lucrative
Feb. 23, 2018 | The New York Times | By Brad Plumer

In Charleston, S.C., where the ports have been expanding to accommodate larger ships sailing through the newly widened Panama Canal, a real-estate developer named Xebec Realty recently went looking for land to build new warehouses and logistics centers.

But first, Xebec had a question: What were the odds that the sites it was considering might be underwater in 10 or 20 years?......Yet detailed information about the city’s climate risks proved surprisingly hard to find. Federal flood maps are based on historical data, and won’t tell you how sea-level rise could exacerbate flooding in the years ahead.....So Xebec turned to a Silicon Valley start-up called Jupiter, which offered to analyze local weather and hydrological data and combine it with climate model projections to assess the potential climate risks Xebec might face in Charleston over the next few decades from things like heavier rainfall, sea level rise or increased storm surge....the reliability of Jupiter's predictive analytics is uncertain....that said, “In economics, information has value if you would make a different decision based on that information,”...... Congress has generally underfunded initiatives such as those at the Federal Emergency Management Agency to incorporate climate change into its federal flood maps.......to get a full picture of flooding risk, you need expertise in weather, but also climate and hydrology and engineering and running complex models on the latest computer hardware,” ... “All of those specialized disciplines are usually heavily siloed within the public sector or the scientific community.”....Jupiter, which acknowledges the uncertainties in climate forecasting, will have to prove that a market exists....flooding and other disasters have led to record losses by insurers.....[Those] losses raised the stakes in terms of trying to get the best possible science on your side when you’re pricing risk,” said John Drzik, president of global risk at Marsh,
climate_change  weather  start_ups  data_driven  forecasting  hard_to_find  predictive_analytics  tools  Charleston  South_Carolina  uncertainty  sea-level_rise  floods  commercial_real_estate  adaptability  specificity  catastrophes  catastrophic_risk  unpredictability  coastal  extreme_weather_events  insurance  FEMA  cartography  floodplains  flood-risk  flood-risk_maps  mapping  historical_data 
february 2018 by jerryking
The path to enlightenment and profit starts inside the office
(Feb. 2, 2016): The Financial Times | John Thornhill.

Competition used to be easy. That is in theory, if not always in practice. Until recently, most competent companies had a clear idea of who their rivals were, how to compete and on what field to fight.

One of the starkest - and scariest - declarations of competitive intent came from Komatsu, the Japanese construction equipment manufacturer, in the 1970s. As employees trooped into work they would walk over doormats exhorting: "Kill Caterpillar!". Companies benchmarked their operations and market share against their competitors to see where they stood.

But that strategic clarity has blurred in so many industries today to the point of near-invisibility thanks to the digital revolution and globalisation. Flying blind, companies seem happier to cut costs and buy back their shares than to invest purposefully for the future. Take the European telecommunications sector. Not long ago most telecoms companies were national monopolies with little, or no, competition. Today, it is hard to predict where the next threat is going to erupt.

WhatsApp, the California-based messaging service, was founded in 2009 and only registered in most companies' consciousness when it was acquired by Facebook for more than $19bn in 2014. Yet in its short life WhatsApp has taken huge bites out of the lucrative text messaging markets. Today, WhatsApp has close to 1bn users sending 30bn messages a day. The global SMS text messaging market is just 20bn a day.

Car manufacturers are rapidly wising up to the threat posed by new generation tech firms, such as Tesla, Google and Uber, all intent on developing "apps on wheels". Chinese and Indian companies, little heard of a few years ago, are bouncing out of their own markets to emerge as bold global competitors.

As the driving force of capitalism , competition gives companies a purpose, a mission and a sense of direction. But how can companies compete in such a shape-shifting environment? There are perhaps two (partial) answers.

The first is to do everything to understand the technological changes that are transforming the world, to identify the threats and opportunities early.

Gavin Patterson , chief executive of BT, the British telecoms group, says one of the functions of corporate leaders is to scan the horizon as never before. "As a CEO you have to be on the bridge looking outwards, looking for signs that something is happening, trying to anticipate it before it becomes a danger."

To that end, BT has opened innovation "scouting teams" in Silicon Valley and Israel, and tech partnerships with universities in China, the US, Abu Dhabi, India and the UK.

But even if you foresee the danger, it does not mean you can deal with it. After all, Kodak invented the first digital camera but failed to exploit the technology. The incentive structures of many companies are to minimise risk rather than maximise opportunity. Innovation is often a young company's game.

The second answer is that companies must look as intensively inwards as they do outwards (e.g. opposing actions). Well-managed companies enjoy many advantages: strong brands, masses of consumer data, valuable historic data sets, networks of smart people and easy access to capital. But what is often lacking is the ambition that marks out the new tech companies, their ability to innovate rapidly and their extraordinary connection with consumers. In that sense, the main competition of so many established companies lies within their own organisations.

Larry Page, co-founder of Google, constantly urges his employees to keep being radical. In his Founders' Letter of 2013, he warned that companies tend to grow comfortable doing what they have always done and only ever make incremental change. "This . . . leads to irrelevance over time," he wrote.

Google operates a 70/20/10 rule where employees are encouraged to spend 70 per cent of their time on their core business, 20 per cent on working with another team and 10 per cent on moonshots. How many traditional companies focus so much on radical ventures?

Vishal Sikka, chief executive of the Indian IT group Infosys, says that internal constraints can often be far more damaging than external threats. "The traditional definition of competition is irrelevant. We are increasingly competing against ourselves," he says.

Quoting Siddhartha by the German writer Hermann Hesse, Mr Sikka argues that companies remain the masters of their own salvation whatever the market pressures: "Knowledge can be communicated. Wisdom cannot." He adds: "Every company has to find its own unique wisdom." [This wisdom reference is reminiscent of Paul Graham's advice to do things that don't scale].

john.thornhill@ft.com
ambitions  brands  breakthroughs  BT  bureaucracies  competition  complacency  constraints  Fortune_500  incentives  incrementalism  Infosys  innovation  introspection  irrelevance  large_companies  LBMA  messaging  mission-driven  Mondelez  moonshots  opposing_actions  organizational_culture  outward_looking  Paul_Graham  peripheral_vision  radical  risk-avoidance  scouting  smart_people  start_ups  staying_hungry  tacit_knowledge  technological_change  threats  uniqueness  unscalability  weaknesses  WhatsApp  wisdom  digital_cameras  digital_revolution  historical_data 
april 2016 by jerryking
Data, Data and More Data
July-August 2013 | Campaigns & Elections | by Colin Delany.

...The picture often portrayed--the Obama campaign as a relentlessly efficient data juggernaut--paints over a lot of workarounds, hacks and improvisations. I'd heard this before, for example at CampaignTech in April, when Obama data manager Ethan Roeder had mentioned that plenty of the campaign's technology was held together with "duct tape and baling wire." He echoed that sentiment in Philadelphia, and he wasn't alone: Obama Chief Scientist Rayid Ghani said that for every mention of "data integration" on the campaign, he had "20 caveats" about how less-than-perfect it actually was in practice...Ghani said that the Obama voter file was actually the smallest data set he'd worked with as a technology professional, in part because people vote so rarely. Elections simply don't come around that often, and compared with commercial marketers (who can draw on thousands of purchases and other transactions to predict buying patterns), political campaigners don't have much historical data to work with.
data  data_driven  political_campaigns  Campaign_2012  Facebook  data_scientists  data_management  historical_data  small_data 
december 2013 by jerryking
Visual Analytics
static data - basic information about ports of entry such as locations, hours of operation, and phone numbers.
historical data - tracking vehicles entering Canada by type, length of stay and port of origin.
real-time data - border wait times, road conditions, weather alerts, Amber alerts, social media postings, information from video cameras at border points
visualization  massive_data_sets  CBSA  crossborder  data  borders  infographics  real-time  historical_data 
december 2012 by jerryking
For SAS, Asia Offers Risks and Potential - WSJ.com
NOV. 21, 2010 | WSJ| By JASON CHOW. "SAS "uses companies'
historical data to work out their futures."...Q: Where is growth in Asia
coming from? A: We do a lot of work in risk management for banks. We
make sure their risk computations are up-to-date and [help them] with
their anti-money laundering. ...We see a lot of growth from the
pharmaceutical sector. SAS has a tool to analyze clinical trials &
effectiveness of a particular drug. We're seeing more pharmaceutical
drug trials move to Asia, esp. in India....Essentially, anybody who's
got data. And lots of it. Of course, there are things like social-media
analysis that don't require your data. We can tell you what people think
of you or your brand without any data from you. We can search out every
blog & tweet that's been done about you for the last 30 days or
whatever time frame, and tell you how people are thinking of your
brand. We call it sentiment analysis. We're having a hard time keeping
up with customer demand on that product.
SAS  Asian  analytics  social_media  reputation  money_laundering  pharmaceutical_industry  sentiment_analysis  risk-management  historical_data 
november 2010 by jerryking
How to be wise before the event
March 9 2009 | Financial Times | By Stefan Stern.

Restraint is back in fashion in these recessionary times. People have lost their appetite for risk.

But hang on a minute. No risk will mean no reward. You need new markets and customers to grow, and that means taking steps into the unknown. I doubt that anyone will be suggesting, in this newspaper’s new series of articles on the future of capitalism, that risk-taking should be abolished.

Bad risk-management helped get us into the current mess. It is vital that we learn the right lessons about risk from the crisis. What are they?

The new edition of Harvard Business Review contains a lucid piece of analysis from René Stulz, professor of banking and monetary economics at Ohio State University’s Fisher College of Business. While his principal focus is on the financial sector, the diagnosis will be helpful to managers in any business or organisation.

Prof Stulz describes six ways in which risk has been mismanaged. First, there has been too much reliance on historical data among today’s decision-makers. Extrapolating from the past can provide, at best, only partial guidance for the future. Financial innovation has created a new world. No wonder some managers were unprepared for the calamitous fall in asset prices and demand. This collapse was unimaginable to anyone basing their thinking on post-war performance alone.

Second, narrow daily measures – in banking these are known as “value at risk” measures – have underestimated the risks that are being run. The assumption behind a daily measure of risk is that action can be taken quickly (through an asset sale) to remove that risk. But, as the current crisis has shown, such rapid moves become impossible when markets seize up.

Third, knowable risks have been overlooked. Managers who work in silos may appreciate the risks that they personally are exposed to. But they may not see how risks being run elsewhere in the business could affect them too. Someone – a chief risk officer? – needs to track them all.

Fourth, concealed risks have been overlooked. Incentives have proved to be particularly dangerous in this regard. Some traders and lenders may have enjoyed taking risky decisions that in the short term appeared to be delivering well for them and their organisations. But they had no incentive to report any downside risk. And unreported risks tend to expand.

Fifth, there has been a failure to communicate effectively. It is dangerous, Prof Stulz says, when risk managers are so expert in their field that they lose the ability to explain in simple terms what they are doing. The board may develop a false sense of security by failing to appreciate the complexity of the risks being managed.

Last, risks have not been managed in real time. Organisations have to be able to monitor fast-changing markets and where necessary respond to them without delay.

Prof Stulz offers a useful technical analysis. But a true understanding of risk also requires a maturity of outlook, an ability to see the big picture, and deep experience. This last is a rare commodity: impossible to fake and acquired only over time.

In a new McKinsey publication called What Matters, the 90-year-old investment manager and author Peter Bernstein offers some sober insights. “What is risk management all about anyway?” he writes. “We use the words as though everybody understands what we are talking about. But life is not that simple. Risk means more things can happen than will happen – which is a fancy way of saying we do not know what is going to happen.”

Mr Bernstein’s central point – not revolutionary, but unarguable – is that downside risks must be assessed rigorously. Someone old enough to remember the Wall Street crash is probably worth listening to right now.[JCK: elder wisdom]

“Nothing is 100 per cent sure,” Mr Bernstein says. “While a 95 per cent probability is statistically significant, that still leaves us in the dark about the remaining 5 per cent; we may decide to accept that uncertainty and bet on the 95 per cent sure thing, but there is still a possibility of being wrong.

“The crucial question to ask is, ‘What would be the consequence if that 5 per cent chance comes to pass?’ ”

Welcome to the less exciting but more soundly based era of calculated risks. For the foreseeable future, business leaders will be trying to be wise before rather than after the event.
beforemath  business  communicating_risks  downside_risks  elder_wisdom  false_sense_of_security  fast-changing  financial_innovation  hidden  historical_data  management  McKinsey  overreliance  Peter_Bernstein  recessions  real-time  risks  risk-assessment  risk-management  Stefan_Stern  the_big_picture  VaR  what_really_matters  wisdom 
may 2009 by jerryking
Six Ways Companies Mismanage Risk - HBR.org
March 2009 |Harvard Business Review | by René M. Stulz
(Charles Waud & WaudWare)
Financial risk management is hard to get right in the best of times. Stulz explores 6 ways institutions usually drop the ball:
1. Relying on Historical Data
2. Focussing on narrow measures
3. Overlooking knowable risks
4. Overlooking concealed risks
5. Failing to communicate
6. Not managing in real time
HBR  risk-management  execution  failure  risks  measurements  unknowns  financial_risk  hidden  latent  Communicating_&_Connecting  signaling  real-time  disclosure  mismanagement  overlooked  historical_data 
march 2009 by jerryking
reportonbusiness.com: Disaster relief
November 28, 2008 at 2:46 PM EST G&M article by DOUG STEINER
Rules for post-disaster investing.
Step 1: Cope and gather new data. Smart people in hurricane-prone areas build defences into their homes and businesses, then watch the weather. Do you do that with your investments?.... Don't invest aimlessly assuming that you'll be able to avoid a crash, then buy at the bottom. I don't know when the next market plunge will happen or how deep it will be, but I'm fortifying my investment castle against disaster by spending less and saving more....Look for new sources of information.
Step 2: Analyze the data. I'm not smart, but I looked at historic data and made a connection-what happens in the U.S. usually happens here, too. We worried enough to sell our house in 2007, but I wasn't disaster-hardened enough to rent, so we bought a smaller house.
Step 3: Consider what country you're in
Step 4: Identify the worst thing that could happen right now. You think Canada's economy is grim? How about the city of Detroit, where the median price of a house or condo dropped to $9,250 (U.S.) in September from $21,250 (U.S.) just a year earlier? Could things get that bad here? Almost certainly not.
Step 5: Act when things stop getting worse (there's an element of "next play" here). Don't wait till they start getting better. If you wait for positive signs, it will be too late. I like hotpads.com, the U.S. real estate search engine with information on foreclosures from RealtyTrac. It lets you swoop across a map of the country like a vulture, looking for distressed properties. I'm not looking in Detroit, but I am interested in Longboat Key, Florida. I'm also combining the online information on foreclosures with updates from a local real estate agent who's desperate for buyers, and who forwards me every property listed in the area.
Step 6: Find out who's ahead of the curve and learn from them. The most interesting financial analysis these days isn't in stock and bond markets-it's in the markets for things like natural disaster insurance. A 2007 study, led by Laurens Bouwer from the Institute of Environmental Studies at Vrije University in Amsterdam (remember that Dutch people living below sea level are keenly interested in floods), includes estimates of the costs of future weather-related disasters. By 2015, potential financial losses from disasters in the world's 10 largest cities will likely climb by up to 88%. Three recommendations: 1) Get more and better data. 2) When adapting to surroundings, take precautions to reduce disaster risk. 3) Find new financial instruments or innovations to spread risks among investors.
Step 7: Invest where the potential returns are highest relative to the risks. Even though stock markets have plunged due to panic, they may not be the most profitable place to put your money in the future. The worst mispricing of assets will almost certainly be in the real estate market, so that's where you may find some of the best bargains. Detroit might turn into a mecca for artists, where $9,000 buys you a house in a neighbourhood that may rebound and thrive. You just have to have the courage to look at the disaster data and act.
ahead_of_the_curve  crisis  dark_side  de-risking  defensive_tactics  disasters  Doug_Steiner  extreme_weather_events  financial_instruments  financial_innovation  first_movers  hacks  historical_data  information_sources  instrumentation_monitoring  investing  lessons_learned  measurements  mispricing  next_play  precaution  risk-sharing  rules_of_the_game  smart_people  thinking_tragically  tips  worst-case 
february 2009 by jerryking

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