The model is not the thing itself. The map is not the territory. Our attempts to turn reality into data are inevitably imperfect, and sometimes they’re way off — like they were last night. On Election Night, everything the experts and their algorithms told us was likely to happen came out different.
Trump’s against-all-predictions win doesn’t mean we should give up on the very idea of empiricism. It does mean that each time we inquire into the state of reality, we should begin with humility. We could always be wrong, and we often will be.
How did our country elect this guy? How? How am I so out of touch with the core of our nation, that I believed this outcome was impossible? How is it that every group I’m engaged with, from the boards I sit on to the conferences I attend, to the friends I eat dinner with, to the band I play with, to the companies I lead and invest in, to the schools and the universities my kids attend, to the pundits I follow…how is it that no one I’ve engaged with in an honest intellectual conversation over the past few months, NO ONE, thought it was possible that this could happen?
Donald Trump won the primaries by thumbing his nose at political convention, including the idea — personified by the folks who steered President Obama’s two winning campaigns — that data science can be used to optimize a presidential campaign. If Trump wins tonight, that upset would also spell a profound defeat for this data-driven mindset (Backchannel).
For one thing, the polls and prediction sites run by numbers nerds all tell us that Trump’s headed for defeat. But proving them wrong is only the beginning of the challenge to a scientific, evidence-driven worldview that a Trump victory would represent.
Al Gore acknowledges the crowd at Web 2 Summit, November 2008
One of the most indelible images of my career was backstage at the Web 2 Summit, the day after Barack Obama was elected president in 2008. I was in the wings of the main stage at the Sheraton Palace hotel in San Francisco. Out in the ballroom, a thousand of technology’s elite stood roaring and jubilant, delivering a standing ovation to the man who had just walked on stage.
Al Gore strode to the podium, grasped it on both sides, looked out into the lights and the crowd, and suddenly — it hit him. Eight years before almost to the day, several hundred hanging chads fluttering in the Florida breeze had stolen his Presidency. The Supreme Court then delivered it to George Bush.
Please vote. Just so you know my bias before reading further, I’m voting for Hillary Clinton.
This post is not aimed at you if you have already decided to vote for Clinton or for Trump. It is aimed at you if you haven’t voted, are considering not voting, or are voting for someone other than Clinton or Trump.
“Oh, what a glorious task we are given, to continually try to improve this great nation of ours.” — President Barack Obama
Public service is championed across many professions. In law, clerking for a federal judge is considered an important part in many lawyers’ careers. Doctors across the country compete for prestigious research and policy roles within government. Their contributions have pushed us forward and made our country stronger. And they’ve become better lawyers and doctors as a result. Now, there’s a huge opportunity for far more technologists to improve the way government serves Americans everywhere. To make vital services like healthcare and benefits more accessible for millions. To add our voice to policy debates on issues of national or local importance. To accelerate our progress and remain the world’s leader in innovative thinking. But this won’t happen on its own.
The first and most important step is for techies to get engaged. This can take a lot of different forms. It can include getting involved in our local communities. Or it could mean applying your rarefied skills as an engineer, designer, UX researcher, product manager (you get the idea) in collaboration with other experts to make the country work better. Our involvement in the future of our country is crucial.
ISIS turns toy drones into killing machines. On the battlefield in Iraq and Syria, ISIS is using hobbyist drones — the kind you can buy on Amazon — to send explosive devices behind enemy lines. Last week they used one to kill two Kurdish fighters (The Washington Post). The development is hardly a surprise; from the smelting of bronze to the splitting of atoms, humanity has always turned its technological breakthroughs into war-fighting tools. The U.S., of course, has been deploying relatively large killer drones for a decade. Now we’re seeing this type of combat make the equivalent of a transition from mainframe to PC scale — and it’s going to be in everyone’s hands. In warfare as in any other kind of competition, every time an innovation comes along, you need to weigh how someone with ill intent might use it against you. Because, sooner or later, they will. As technology writer James Gleick asked on Twitter: “Did we think we were going to perfect a cheap, lethal technology and keep it to ourselves?”
Obama wants a government stake in our AI future. As artificial intelligence and machine learning move into the mainstream of our lives, driving our cars and our business decisions, how do we make sure they have human values embedded in them? President Obama ponders that question in conversation with MIT Media Lab director Joi Ito (the interview is part of the issue of Wired that Obama has guest-edited). There have been times, during Obama’s eight years in the Oval Office, that you might have mistaken the president, a formidably rational decision-maker with a Spock-like cool, for an AI himself. Here he talks about open data, cyber-security, and post-automation employment with an easy familiarity and depth that suggests his interest lies deeper than a briefing memo. If we rely only on the private sector to build the AI future, Obama warns, we could end up with systems that don’t fully represent our society. As Ito says, “It’s been a predominately male gang of kids, mostly white, who are building the core computer science around AI, and they’re more comfortable talking to computers than to human beings.” Obama’s response: “If we want the values of a diverse community represented in these breakthrough technologies, then government funding has to be a part of it.” Today the White House also released two reports on AI (Quartz), focusing on human-machine collaboration, how to boost jobs, and ethics and transparency.
The energy industry is on the cusp of a revolution. Solar power prices continue to fall, monolithic power stations look financially foolhardy, and electric vehicles and better battery storage are no longer just a dream. Last year’s Paris Climate Agreement also injected fresh urgency into efforts to tackle climate change. And consumers are sick of paying over the odds to heat and power their homes.
Energy suppliers are well aware of the impending disruption to their industry. According to the PriceWaterhouseCoopers (PwC) Global Power & Utilities Survey 2015, 97% expect to see a medium to very high level of market disruption by 2020, 73% anticipate major or very major business model transformation by 2030, and 60% say their main home market will be more than ‘50% transformed’ by 2030.
Markets are putting Deutsche Bank through a safety drill. If we’re lucky, the rustle of investors fleeing Deutsche Bank late this week will prove to be a minor hiccup in the world of capital. If we’re unlucky, it will be the first domino to fall in another wave of financial disaster like the one we experienced in 2008. Deutsche Bank’s recent round of woes started with a $14 billion fine by the U.S. government for the bank’s sale of mortgage-backed securities during that last bank crisis, which sent investors for the doors (Fortune). Along with the recent scandal at Wells Fargo, which revealed that thousands of its employees had for years been opening fake accounts to meet sales incentives, Deutsche Bank’s problems remind us that, as a result of hard lessons learned a decade ago, our banking system’s safety protections got some upgrades, but they haven’t actually been tested yet. And if they’re not up to the next crisis, then we’re all going to be stuck paying the price — again.
When is a poll not a poll? When it’s an online survey in which anyone can vote and vote again. One of the foundations of data science took a beating in the political arena this week, as Donald Trump crowed over his wins in snap post-debate online “polls” even as the real polls started tilting in his opponent’s favor (CNN). Real polls, scientific ones, try to map the reality of public opinion through a process of weighted sampling. You might only ask 1000 people what they think; but if those thousand respondents match the national population in race and religion, party affiliation, income, and so on — or, if they don’t, you weight them a bit so they do — you’ve got a snapshot of something real. But if you just open the tap on the internet and ask anyone to vote, your results are nearly worthless. Trump’s wins are like Hank the Angry Drunken Dwarf’s victory in People’s “Most Beautiful People” online poll; a self-selected sample is just a gauge of partisan excitement level. In a larger sense, this overvaluing of online polls reflects our deeper confusion over how to use all kinds of metrics. By turning yardsticks into targets, we break them (Quartz). Your poll becomes someone else’s campaign; your Key Performance Indicator stops telling you anything useful because everyone in your organization is trying to game it. Without context and understanding, raw data is worse than useless — it can be toxic.
Lately I’ve been writing about the relative virtues of basic income and child allowance proposals to counteract poverty and inequality. These seem like novel ideas on the American scene today. But in fact, there was a time when both of these ideas were seriously proposed on Capitol Hill. After forty-five years of lost faith in government, we are simply rediscovering the ambitions we once held.
In August 1969, President Richard Nixon unveiled a basic income scheme for needy families with children called the “Family Assistance Plan.” (FAP) Under Nixon’s FAP, a family of four would receive $1,600 annually from the federal government, or about $10,500 in 2016 dollars. For families deriving income from work, the FAP would gradually phase out above a certain level. Indeed, FAP included a work requirement for most “employable” individuals.
