You have doppelgängers. They’re quietly influencing your life.
Companies refer to like-minded strangers when recommending products to you.
Seth Stephens-Davidowitz has used data from the internet, particularly Google searches, to get new insights into the human psyche. A book summarizing his research, Everybody Lies, was published in May 2017 by HarperCollins.
Seth has used Google searches to measure racism, self-induced abortion, depression, child abuse, hateful mobs, the science of humor, sexual preference, anxiety, son preference, and sexual insecurity, among many other topics.
He worked for one-and-a-half years as a data scientist at Google and is currently a contributing op-ed writer for the New York Times. He is designing and teaching a course about his research at The Wharton School at the University of Pennsylvania, where he will be a visiting lecturer.
Seth received his BA in philosophy, Phi Beta Kappa, from Stanford, and his PhD in economics from Harvard. In high school, he wrote obituaries for the local newspaper, the Bergen Record, and was a juggler in theatrical shows. He now lives in Brooklyn and is a passionate fan of the Mets, Knicks, Jets, Stanford football, and Leonard Cohen. For more info, head to sethsd.com.
SETH STEPHENS-DAVIDOWITZ: So there's a methodology called k-Nearest Neighbor in big data analysis where you can find a person who looks similar to another person. Who's the most similar on a number of traits?
But I kind of renamed the search a doppelganger search because I think that's a cooler name for it and also accurate. So you basically look in a huge data set, you take a person and say "Who is the person who looks most similar to that person?" So one way you might use this is if Amazon's looking for what books to recommend. They may find your book-reading doppelganger. So across the whole universe of Amazon customers, who's the person who tends to buy books like you have bought? And then what books has that person recently read and enjoyed that you haven't read and enjoyed? And that's sort of how they recommend books to you. And this can be used in a lot of other areas. People are just starting to use this in health where you can say, across the entire universe of patients who has symptoms very similar to your symptoms, and what has worked for those people, are your health doppelgangers. So it's a very powerful methodology and it gets more powerful the more data you have. Because the more data you have the more similar, the more likely you're going to find someone in that data set who's really, really similar to you.
Some of this stuff, some of the big data analysis are things we have always kind of done. That's kind of what doctors try to do. They try to say, "Who are you similar to? Of all the patients I've seen, which ones remind me of your case, and what worked for them?" But they've been doing this on a small number of patients, namely the ones they've seen. Whereas the potential for big data is you can do it over the entire universe of patients and get people who are, really, much, much more similar to you. Really zoom in on the tiny subset of people who have a very similar path to you. Instead of saying "You have the condition depression" which might remind a doctor of a hundred depressed patients that he's seen over the past couple of years, you can say maybe that "You have a particular type of depression." So you maybe sleep all the time whereas other depressed patients don't sleep all the time, and you feel guilty whereas other depressed patients don't feel guilty, and then really find these people who are really, really similar who's depression has taken a much more similar path to yours than have other people's depressions.
- One way companies recommend products to you is by referring the purchasing tendencies of individuals who have bought similar items in past. When these individuals have many similarities, they are referred to as doppelgangers.
- This can also work in medicine. When someone gets sick, professionals may refer to the patient's health doppelganger, who's had similar symptoms, and prescribe treatments that previously worked.
- It's a powerful methodology and it gets more powerful the more data you have. That is, the more data you have, the more likely you're going to find someone in that data set who's "really, really" similar to you.
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The COVID-19 pandemic is making health disparities in the United States crystal clear. It is a clarion call for health care systems to double their efforts in vulnerable communities.
- The COVID-19 pandemic has exacerbated America's health disparities, widening the divide between the haves and have nots.
- Studies show disparities in wealth, race, and online access have disproportionately harmed underserved U.S. communities during the pandemic.
- To begin curing this social aliment, health systems like Northwell Health are establishing relationships of trust in these communities so that the post-COVID world looks different than the pre-COVID one.
COVID-19 deepens U.S. health disparities<p>Communities on the pernicious side of America's health disparities have their unique histories, environments, and social structures. They are spread across the United States, but they all have one thing in common.</p><p>"There is one common divide in American communities, and that is poverty," said <a href="https://www.northwell.edu/about/leadership/debbie-salas-lopez" target="_blank">Debbie Salas-Lopez, MD, MPH</a>, senior vice president of community and population health at Northwell Health. "That is the undercurrent that manifests poor health, poor health outcomes, or poor health prognoses for future wellbeing."</p><p>Social determinants have far-reaching effects on health, and poor communities have unfavorable social determinants. To pick one of many examples, <a href="https://www.npr.org/2020/09/27/913612554/a-crisis-within-a-crisis-food-insecurity-and-covid-19" target="_blank" rel="noopener noreferrer">food insecurity</a> reduces access to quality food, leading to poor health and communal endemics of chronic medical conditions. The U.S. Centers for Disease Control and Prevention has identified some of these conditions, such as obesity and Type 2 diabetes, as increasing the risk of developing a severe case of coronavirus.</p><p>The pandemic didn't create poverty or food insecurity, but it exacerbated both, and the results have been catastrophic. A study published this summer in the <em><a href="https://link.springer.com/article/10.1007/s11606-020-05971-3" target="_blank">Journal of General Internal Medicine</a></em> suggested that "social factors such as income inequality may explain why some parts of the USA are hit harder by the COVID-19 pandemic than others."</p><p>That's not to say better-off families in the U.S. weren't harmed. A <a href="https://voxeu.org/article/poverty-inequality-and-covid-19-us" target="_blank" rel="noopener noreferrer">paper from the Centre for Economic Policy Research</a> noted that families in counties with a higher median income experienced adjustment costs associated with the pandemic—for example, lowering income-earning interactions to align with social distancing policies. However, the paper found that the costs of social distancing were much greater for poorer families, who cannot easily alter their living circumstances, which often include more individuals living in one home and a reliance on mass transit to reach work and grocery stores. They are also disproportionately represented in essential jobs, such as retail, transportation, and health care, where maintaining physical distance can be all but impossible.</p><p>The paper also cited a positive correlation between higher income inequality and higher rates of coronavirus infection. "Our interpretation is that poorer people are less able to protect themselves, which leads them to different choices—they face a steeper trade-off between their health and their economic welfare in the context of the threats posed by COVID-19," the authors wrote.</p><p>"There are so many pandemics that this pandemic has exacerbated," Dr. Salas-Lopez noted.</p><p>One example is the health-wealth gap. The mental stressors of maintaining a low socioeconomic status, especially in the face of extreme affluence, can have a physically degrading impact on health. <a href="https://www.scientificamerican.com/index.cfm/_api/render/file/?method=inline&fileID=123ECD96-EF81-46F6-983D2AE9A45FA354" target="_blank" rel="noopener noreferrer">Writing on this gap</a>, Robert Sapolsky, professor of biology and neurology at Stanford University, notes that socioeconomic stressors can increase blood pressure, reduce insulin response, increase chronic inflammation, and impair the prefrontal cortex and other brain functions through anxiety, depression, and cognitive load. </p><p>"Thus, from the macro level of entire body systems to the micro level of individual chromosomes, poverty finds a way to produce wear and tear," Sapolsky writes. "It is outrageous that if children are born into the wrong family, they will be predisposed toward poor health by the time they start to learn the alphabet."</p>Research on the economic and mental health fallout of COVID-19 is showing two things: That unemployment is hitting <a href="https://www.pewsocialtrends.org/2020/09/24/economic-fallout-from-covid-19-continues-to-hit-lower-income-americans-the-hardest/" target="_blank" rel="noopener noreferrer">low-income and young Americans</a> most during the pandemic, potentially widening the health-wealth gap further; and that the pandemic not only exacerbates mental health stressors, but is doing so at clinically relevant levels. As <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7413844/" target="_blank" rel="noopener noreferrer">the authors of one review</a> wrote, the pandemic's effects on mental health is itself an international public health priority.
Working to close the health gap<img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yNDc5MDk1MS9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTYxNTYyMzQzMn0.KSFpXH7yHYrfVPtfgcxZqAHHYzCnC2bFxwSrJqBbH4I/img.jpg?width=980" id="b40e2" class="rm-shortcode" data-rm-shortcode-id="1b9035370ab7b02a0dc00758e494412b" data-rm-shortcode-name="rebelmouse-image" />
Northwell Health coronavirus testing center at Greater Springfield Community Church.
Credit: Northwell Health<p>Novel coronavirus may spread and infect indiscriminately, but pre-existing conditions, environmental stressors, and a lack of access to care and resources increase the risk of infection. These social determinants make the pandemic more dangerous, and erode communities' and families' abilities to heal from health crises that pre-date the pandemic.</p><p>How do we eliminate these divides? Dr. Salas-Lopez says the first step is recognition. "We have to open our eyes to see the suffering around us," she said. "Northwell has not shied away from that."</p><p>"We are steadfast in improving health outcomes for our vulnerable and underrepresented communities that have suffered because of the prevalence of chronic disease, a problem that led to the disproportionately higher death rate among African-Americans and Latinos during the COVID-19 pandemic," said Michael Dowling, Northwell's president and CEO. "We are committed to using every tool at our disposal—as a provider of health care, employer, purchaser and investor—to combat disparities and ensure the <a href="https://www.northwell.edu/education-and-resources/community-engagement/center-for-equity-of-care" target="_blank" rel="noopener noreferrer">equity of care</a> that everyone deserves." </p><p>With the need recognized, Dr. Salas-Lopez calls for health care systems to travel upstream and be proactive in those hard-hit communities. This requires health care systems to play a strong role, but not a unilateral one. They must build <a href="https://www.northwell.edu/news/insights/faith-based-leaders-are-the-key-to-improving-community-health" target="_blank" rel="noopener noreferrer">partnerships with leaders in those communities</a> and utilize those to ensure relationships last beyond the current crisis. </p><p>"We must meet with community leaders and talk to them to get their perspective on what they believe the community needs are and should be for the future. Together, we can co-create a plan to measurably improve [community] health and also to be ready for whatever comes next," she said.</p><p>Northwell has built relationships with local faith-based and community organizations in underserved communities of color. Those partnerships enabled Northwell to test more than 65,000 people across the metro New York region. The health system also offered education on coronavirus and precautions to curb its spread.</p><p>These initiatives began the process of building trust—trust that Northwell has counted on to return to these communities to administer flu vaccines to prepare for what experts fear may be a difficult flu season.</p><p>While Northwell has begun building bridges across the divides of the New York area, much will still need to be done to cure U.S. health care overall. There is hope that the COVID pandemic will awaken us to the deep disparities in the US.</p><p>"COVID has changed our world. We have to seize this opportunity, this pandemic, this crisis to do better," Dr. Salas-Lopez said. "Provide better care. Provide better health. Be better partners. Be better community citizens. And treat each other with respect and dignity.</p><p>"We need to find ways to unify this country because we're all human beings. We're all created equal, and we believe that health is one of those important rights."</p>
Researchers make the case for "deep evidential regression."
- MIT researchers claim that deep learning neural networks need better uncertainty analysis to reduce errors.
- "Deep evidential regression" reduces uncertainty after only one pass on a network, greatly reducing time and memory.
- This could help mitigate problems in medical diagnoses, autonomous driving, and much more.
Credit: scharsfinn86 / Adobe Stock<p>On the road, 1 percent could be the difference between stopping at an intersection or rushing through just as another car runs a stop sign. Amini and colleagues wanted to produce a model that could better detect patterns in giant data sets. They named their solution "deep evidential regression."</p><p>Sorting through billions of parameters is no easy task. Amini's model utilizes uncertainly analysis—learning how much error exists within a model and supplying missing data. This approach in deep learning isn't novel, though it often takes a lot of time and memory. Deep evidential regression estimates uncertainty after only one run of the neural network. According to the team, they can assess uncertainty in both input data <em>and</em> the final decision, after which they can either address the neural network or recognize noise in the input data.</p><p>In real-world terms, this is the difference between trusting an initial medical diagnosis or seeking a second opinion. By arming AI with a built-in detection system for uncertainty, a new level of honesty with data is reached—in this model, with pixels. During a test run, the neural network was given novel images; it was able to detect changes imperceptible to the human eye. Ramini believes this technology can also be used to pinpoint <a href="https://www.theguardian.com/technology/2020/jan/13/what-are-deepfakes-and-how-can-you-spot-them" target="_blank">deepfakes</a>, a serious problem we must begin to grapple with.</p><p>Any field that uses machine learning will have to factor in uncertainty awareness, be it medicine, cars, or otherwise. As Amini says, </p><p style="margin-left: 20px;">"Any user of the method, whether it's a doctor or a person in the passenger seat of a vehicle, needs to be aware of any risk or uncertainty associated with that decision."</p><p>We might not have to worry about alien robots turning on us (yet), but we should be concerned with that new feature we just downloaded into our electric car. There will be many other issues to face with the emergence of AI in our world—and workforce. The safer we can make the transition, the better. </p><p>--</p><p><em>Stay in touch with Derek on <a href="http://www.twitter.com/derekberes" target="_blank">Twitter</a> and <a href="https://www.facebook.com/DerekBeresdotcom" target="_blank" rel="noopener noreferrer">Facebook</a>. His new book is</em> "<em><a href="https://www.amazon.com/gp/product/B08KRVMP2M?pf_rd_r=MDJW43337675SZ0X00FH&pf_rd_p=edaba0ee-c2fe-4124-9f5d-b31d6b1bfbee" target="_blank" rel="noopener noreferrer">Hero's Dose: The Case For Psychedelics in Ritual and Therapy</a>."</em></p>
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Vegans and vegetarians often have nutrient deficiencies and lower BMI, which can increase the risk of fractures.
- The study found that vegans were 43% more likely to suffer fractures than meat eaters.
- Similar results were observed for vegetarians and fish eaters, though to a lesser extent.
- It's possible to be healthy on a vegan diet, though it takes some strategic planning to compensate for the nutrients that a plant-based diet can't easily provide.
Comparison of fracture cases by diet group
Credit: Tong et al.<p>The results showed that vegans were especially vulnerable to hip fractures, suffering 2.3 times more cases than meat-eaters. Vegetarians and pescatarians were also more likely to suffer hip fractures, though to a lesser extent.</p><p>One explanation may be that non-meat eaters consume less calcium and protein. Calcium helps the body build strong bones, particularly before age 30, after which the body begins to lose bone mineral density (though consuming enough calcium through diet or supplement can <a href="https://ods.od.nih.gov/factsheets/Calcium-Consumer/" target="_blank">help offset losses</a>). Lower bone mineral density means higher risk of fracture.</p><p>Protein seems to help the body absorb calcium, <a href="https://www.bonejoint.net/blog/did-you-know-that-certain-foods-block-calcium-absorption/#:~:text=Historically%2C%20nutritionists%20have%20warned%20that,may%20increase%20intestinal%20calcium%20absorption." target="_blank" rel="noopener noreferrer">when consumed in normal levels</a>. The recent study, along with past research, shows that people who don't eat meat tend to have lower levels of both protein and calcium. When the researchers accounted for non-meat eaters who supplemented their diets with calcium and protein, fracture risk decreased, but still remained significant.</p>
Credit: Pixabay<p>Another explanation is body mass index (BMI). Non-meat eaters tend to have a lower BMI, which is associated with higher fracture risk, particularly hip fractures. In the new study, vegans with a low BMI were especially likely to suffer hip fractures. That might be because having more body mass provides a cushioning effect when people fall.</p><p>Still, the study has some limitations. For one, White European women were overrepresented in the sample. The researchers also didn't collect precise data on the type of calcium or protein supplementation, diet quality or causes of fractures.</p><p>Another complicating factor: Producers of vegan products, such as plant-based milk, are increasingly fortifying foods with nutrients like calcium and protein, so modern vegans are potentially at lower risk of deficiency.</p><p>The researchers wrote that their findings "suggest that bone health in vegans requires further research."</p>