Fair Shot Page 6

  I assumed he was joking, but all of a sudden the local staff were saying, “Let’s do it!” I looked at a colleague who had accompanied me across the world. Her look back at me confirmed that they were indeed crazy. “How about we give it 15 minutes instead?” I said. We bought a Fanta from a shack nearby and settled in.

  This was my third trip to Kenya and my second to the GiveDirectly villages. My first had happened a year earlier. After I read Holden’s blog post, my curiosity about cash transfers had grown quickly. Over the next several months, I had followed every lead I could find into the world of “cash assistance.” It turned out there was an entire field dedicated to the topic, and several books and hundreds of reports had been written about experimental cash transfer programs all over the world. Michael and another economist, Paul Niehaus, had recently started GiveDirectly to enable American donors to give cash away to those who needed it most. While working on their PhDs at Harvard, they had grown suspicious of the effectiveness of many aid programs. Hundreds of studies and their own instincts told them that cash might be a more powerful tool to help the poor than traditional programs, but no American charity would allow them to give directly to the people most in need.

  They decided to do it themselves. In 2010, they began distributing their own money to families—$1,000 to each, with no strings attached—who lived in the slums around Nairobi on less than a dollar a day. They incorporated GiveDirectly as a charity the same year and began raising money from outside donors as well. I connected with Michael and Paul soon after, through what was then GiveDirectly’s extremely basic website. Paul, an award-winning economist, moonlighted as a coder and had built the website himself. Light on photos, heavy on statistics, and generally clunky, it was the exact opposite of every nonprofit website I had seen over the previous few years, and I loved it. Clearly, they were uninterested in marketing, and they had no plan for donor cultivation or management. They scoffed at the idea of a gala or a glossy annual report and questioned everything about the traditional nonprofit model. They purposefully made themselves unappealing to the vast majority of donors so they could focus on a smaller set that valued performance over pop. Within months, I gave my first $100,000, and GiveDirectly in turn sent $90,000 of that—via text message—to 90 families who had been living on less than $1 a day. (They limit staff costs and overhead to 10 percent of each dollar given.) This was as close to literally handing out money as I could come.

  An hour after the van had gotten underway again, it pulled over to the side of the road. There were no huts in sight, and no evidence of human civilization outside of a few Kenyan women carrying parcels and walking alongside the road. The local staff member who had organized the expedition hopped out of the van, gestured toward the horizon, and said, “This way!” She set out, and the rest of us fell in line behind her.

  After a 20-minute walk through the bush, brambles nipping at our legs, we finally arrived at a set of red-earth huts. All of the people who lived in this tiny village had received cash transfers over the past year—two payments of roughly $500, made via M-Pesa, a mobile service that enables easy money transfers. The digital money can be converted to traditional paper currency at any time. The villages that GiveDirectly serves are not directly connected to paved roads, and most do not have basic infrastructure like electricity or running water. Most of the villagers are engaged in subsistence farming and fishing.

  When GiveDirectly takes donors or journalists on tours of these villages, they don’t prescreen recipients to prepare and package the best stories, but instead choose the huts at random. You don’t always meet the most talkative people or hear the most riveting stories, and a lot of times, no one is home. But instead of marketing pizzazz, you see a more representative sample of the beneficiaries, and you know that you are not just being sold a bill of goods.

  We split up into two groups so as not to overwhelm the recipients. My group ducked into a hut with a new aluminum roof (most of the huts we had seen on the walk over were thatched). The woman who sat across from us was nearly six feet tall and wore a simple cotton dress, yellow plastic sandals, and had a scarf tied on top of her head. She was very quiet, almost whispering her responses to our questions. She had lived in the hut for a decade, she told us, and her husband spent much of his time fishing on Lake Victoria. Her children were grown. They had used half of their transfer to replace their thatch roof with aluminum. The average amount saved in ongoing repair costs was $110 annually, meaning their investment would pay off in a few years. She had used the rest of the transfer for food and as a gift to her kids.

  We had similar conversations in the next two homes we visited. Another family had installed a solar-powered lightbulb in their hut so their kids could do schoolwork in the evenings. One recipient said to us, through the translator, that another charity had given him a cow. “What am I going to do with a cow? Now I have to feed it and take care of it!” He didn’t need or want livestock, but a charity had decided that he should have it, regardless of his interest or ability to maintain it. All of the homes had different-color chalk markings on the doors, evidence of all of the other nonprofits who had come through at one point or another with some kind of service to provide or good to give out. Where were they now?

  Another recipient our companions talked to that day, a young bachelor, was the entrepreneurial type. Saturday nights in Kenya, like Saturday nights in a lot of other places in the world, are a time to rest and unwind after a busy week. Friends of his threw parties or celebrations with sodas, sweets, and beer. They used a small radio to play music, but the sound was often scrambled with static. He believed he could do better, so he used his first transfer to buy a keyboard. It enabled him to perform as a musician and DJ, and he charged the partygoers a small fee. With the second transfer he invested in an unrelated and similarly creative idea. He spent some of the money on livestock and used the rest to buy a beehive. Everybody wanted fresh and cheap honey, and he didn’t mind the occasional beesting. His apiary provided him another independent revenue stream.

  In contrast to the integrated service delivery model in the Millennium Villages, with its costly overhead and UN-approved white papers, GiveDirectly was doing something painfully simple and obvious: letting the people in need decide for themselves. Village residents could pool their money to build a well, use the funds for school fees, or invest in their homes. Not every decision would be wise, but it seemed like this kind of investment respected their local knowledge and their ability to direct their own lives.

  And the evidence shows that on balance, cash transfers like these are more effective at improving the lives of the communities they serve than other aid interventions. In 2011, GiveDirectly’s leadership enlisted independent researchers affiliated with MIT’s Poverty Action Lab to assess the impact of their transfers. The analysis was done in coordination with the independent nonprofit Innovations for Poverty Action and the National Institutes of Health. The study analyzed the impact of cash transfers using a randomized control trial, the same methodology that pharmaceutical companies use to assess the power of a new drug and its side effects. The researchers surveyed recipients before they received the money to establish a baseline and again afterward to understand the impact. They then compared those villages to a set of “control” villages that did not receive transfers. The design of the study was pre-announced so it was impossible to bury unflattering data, and the researchers opened their raw data sets to the world. They even paid independent researchers to comb through it to find errors or inconsistencies.

  Even though the study had a relatively short time horizon of two years, the researchers documented significant positive effects on the cash recipients’ assets, earnings, food security, mental health, and female empowerment. The income of families increased by 27 percent, and the value of the assets that they held, like livestock and their homes, increased by $430, a significant amount for people who live on less than a dollar a day. Addition
al spending on nutrition significantly reduced the families’ food insecurity index, a measurement of meals skipped and diet quality.

  Perhaps most importantly, the recipients were happier. The researchers used a psychological well-being index that was a weighted average of the participants’ responses to an internationally standardized questionnaire. They found a significant increase in self-reported life satisfaction. A reporter at Business Insider summarized the results: “People who received the money were happier, more satisfied with life, less stressed, and depressed less often.”

  The researchers also found that recipients of the benefit, along with their neighbors who did not receive the benefit but lived in the same village, scored higher on a female empowerment index that measures things like domestic violence rates and attitudes toward men. They are now doing a longer-term assessment to see if they can replicate the outcome, but these studies suggest that having more economic security lowers the overall stress level in a home and the rate of domestic violence.

  Interestingly, the study showed no increase in the amount of alcohol and tobacco consumed. Skeptical that participants would give an honest answer to the question, the researchers used a different methodology to assess the use of these so-called temptation goods. They presented a list of five common activities, like talking on the phone or visiting friends, and then asked how many of these activities the respondents had done in the past week. One group was presented with a list that did not include alcohol and tobacco, another with the list plus alcohol, and a third with the list plus tobacco. The question the respondents answered was, “Have you participated in any of these five activities in the past week?” and the respondents did not need to specify which, if any, they had. The researchers compared the responses across different groups and found no increased likelihood that cash recipients consumed more alcohol or tobacco than the control group.

  GiveDirectly’s study is a drop in the research bucket when it comes to cash. Over the past few decades, nearly 200 other studies have been conducted on 56 different kinds of cash transfer programs, and they have produced a variety of results based on the amount and frequency of the transfer, who receives it, and how long they receive it for. A recent review of all of these studies by the Overseas Development Institute found several consistent effects: cash transfers reduce immediate poverty and increase savings, raise school attendance, cause recipients to use health services more frequently, and are associated with a reduction in child labor. Most studies show no effect on the amount of time adults work, and some show people work more. Another review of all cash studies by the World Bank showed no evidence that cash transfers affect drinking or smoking behavior.

  Aid organizations like the International Rescue Committee (IRC) and World Food Programme (WFP) have caught on. Over the past five years, WFP has migrated a massive portion of its budget, nearly $900 million in 2016, to providing people cash rather than bowls of rice. “WFP takes the view that it is the people it serves who are in a position to decide what is best for them,” the organization says in its review of the power of cash. “Cash-based transfers help by giving the purchasing power to the people.” The IRC has similarly put cash allowances at the center of how it responds to refugee crises across the world, providing cash to Iraqi families newly liberated from ISIS and refugees from the Middle East and North Africa stranded in Greece. It has committed to distribute a quarter of its humanitarian aid as cash transfers by 2020, up from around 6 percent when the announcement was made in 2015.

  The amount of cash benefits that humanitarian organizations provide is still small, but it has grown by a factor of five in a little more than a decade. At the same time, American donors interested in extreme poverty have gotten behind GiveDirectly’s work. In 2012, when I began donating, the organization raised $500,000 total. In 2015 and 2016, GiveDirectly raised more than $90 million to fund its programs.

  A sea change in international development is reshaping the sector. In the year after I returned from Africa, I watched as the idea caught fire. The GiveDirectly experiments had been one catalyst, but other cash programs in Brazil and Mexico had sparked a robust conversation about the best way to help the poor and middle class in developing economies. Iran cashed in all of its complex food and energy subsidies to create the first nationwide cash transfer program, and India is considering doing the same. The IRC began to pilot cash transfer programs in disaster and humanitarian relief zones, and global think tanks produced new reports assessing the power of cash to transform lives. Most of the analyses came to the same conclusion: cash is one of the most powerful ways to lift people out of poverty. It is not a panacea, but in many cases, it should be the centerpiece of aid programs in conjunction with other supports like schools and hospitals.

  At the same time that cash was becoming increasingly ascendant in international circles, I was paying more attention to the brewing economic problems in the United States. The United States has little in common with a country like Kenya, where GiveDirectly works. Our economy is 265 times larger, and our government and social services are significantly more robust. It feels like a stretch to compare the work of a small international nonprofit like GiveDirectly to American government programs.

  But as I grew increasingly inspired by the power of cash internationally, I wondered how cash transfers might beat back the economic forces that had created historic inequality in our own country. The scale of the problem was much larger and more expensive, and I quickly realized that any long-term solution would need to shift public policy and not just rely on philanthropy to reach everyone who needed it.

  To my surprise, I discovered that the United States already runs the biggest cash transfer program in the world, giving tens of billions of dollars, no strings attached, to struggling poor families to help boost their incomes and stabilize their financial lives. We don’t talk about it much, but we have good, home-grown evidence that aligns with the international studies’ conclusions: that this money is well spent and lifts education and health outcomes for recipients here, just as it does abroad. And by tweaking and expanding it, we could make it possible for all American families to make ends meet.

  4

  The Precariat

  Over the past couple years, many technology and business leaders have come to believe we need a guaranteed income because of the threat of artificial intelligence. Elon Musk and Richard Branson, for instance, believe that “intelligent” machines may soon create a new era of mass unemployment. In that world, they argue, there will be no choice but to help people meet their basic needs.

  These leaders aren’t contemplating a future of wholesale job destruction in order to be contrarian or controversial. They see a meaningful difference between the impacts of emerging artificial intelligence and the automation we have already come to know. Whereas automation is what we generally think of with technology—robotic arms and ATMs—artificial intelligence is the capacity for algorithms or machines to learn for themselves. They are increasingly able to incorporate feedback from their actions and to adjust future behavior, simulating a kind of intelligence. For instance, Facebook’s photo software will scan a photo you took, match it to its existing database, and then suggest that you tag that photo “Mom.” When you give it an answer, “Yes, that’s my Mom,” or “No, that’s not her,” it incorporates whether or not it got its initial prediction right into the algorithm that powered the initial match. Next time it will know better if a person with that facial structure is “Mom.” The same goes with Google’s translation software or Amazon’s Echo devices, which are constantly incorporating feedback into their future performance plans. Tesla’s self-driving cars improve their driving ability by collecting, storing, and analyzing all of the driving data they receive while cars are on the road. These systems aren’t just automating processes: they are growing smarter over time.

  There is little doubt that artificial intelligence could destroy many jobs in the
future, but I’m not sure they will. Self-driving cars could replace human drivers, and smart bots might replace personal assistants. The white-collar jobs of doctors and nurses, teachers, and lawyers might be radically reshaped with the introduction of smarter technologies. But all of these things fall in the category of “might” happen, and there are plenty of experts who believe there is little reason to believe in the hype of artificial intelligence. They do not believe the claims that “this time is different.”

  Before President Barack Obama left office, I was a guest at a small dinner in Washington, D.C., at the Brookings Institution, a well-respected policy think tank. I was the youngest guest in the room by far, and the only one not wearing the Washington uniform of suit and tie. Jason Furman, then the chair of the president’s Council of Economic Advisers, was discussing “digital competitiveness” in today’s economy. Midway through Furman’s presentation, I found an opening to ask, “What are you doing to plan for a future with more artificial intelligence where there might be fewer jobs?” He paused, barely concealing his annoyance with such a predictable question, coming from such a predictable source, even though I was skeptical of the claim myself. “Three hundred years of economic history tells us that can’t be true,” he said curtly. It was the only question he answered that night with a single sentence. This is one area of rare agreement between the Obama economic team and Donald Trump’s administration. Steve Mnuchin, Trump’s treasury secretary, said last year that he was “not at all” worried about job displacement at the hands of technology. “In terms of artificial intelligence taking American jobs, I think we’re, like, so far away from that—not even on my radar screen,” Mnuchin said. “I think it’s 50 or 100 more years.”