Following the people and events that make up the research community at Duke

Category: Data Page 1 of 9

Opening the Black Box: Duke Researchers Discuss Bias in AI

Sticky post

Artificial intelligence has not only inherited many of the strongest capabilities of the human brain, but it has also proven to use them more efficiently and effectively. Object recognition, map navigation, and speech translation are just a few of the many skills that modern AI programs have mastered, and the list will not stop growing anytime soon.

Unfortunately, AI has also magnified one of humanity’s least desirable traits: bias. In recent years, algorithms influenced by bias have often caused more problems than they sought to fix.

When Google’s image recognition AI was found to be classifying some Black people as gorillas in 2015, the only consolation for those affected was that AI is improving at a rapid pace, and thus, incidents of bias would hopefully begin to disappear. Six years later, when Facebook’s AI made virtually the exact same mistake by labeling a video of Black men as “primates,” both tech fanatics and casual observers could see a fundamental flaw in the industry.

Jacky Alciné’s tweet exposing Google’s racist AI algorithm enraged thousands in 2015.


On November 17th, 2021, two hundred Duke Alumni living in all corners of the world – from Pittsburgh to Istanbul and everywhere in between – assembled virtually to learn about the future of algorithms, AI, and bias. The webinar, which was hosted by the Duke Alumni Association’s Forever Learning Institute, gave four esteemed Duke professors a chance to discuss their view of bias in the artificial intelligence world.

Dr. Stacy Tantum, Bell-Rhodes Associate Professor of the Practice of Electrical and Computer Engineering, was the first to mention the instances of racial bias in image classification systems. According to Tantum, early facial recognition did not work well for people of darker skin tones because the underlying training data – observations that inform the model’s learning process – did not have a broad representation of all skin tones. She further echoed the importance of model transparency, noting that if an engineer treats an AI as a “black box” – or a decision-making process that does not need to be explained – then they cannot reasonably assert that the AI is unbiased.

Stacy Tantum, who has introduced case studies on ethics to students in her Intro to Machine Learning Class, echoes the importance of teaching bias in AI classrooms.

While Tantum emphasized the importance of supervision of algorithm generation, Dr. David Hoffman – Steed Family Professor of the Practice of Cybersecurity Policy at the Sanford School of Public Policy – explained the integration of algorithm explainability and privacy. He pointed to the emergence of regulatory legislation in other countries that ensure restrictions, accountability, and supervision of personal data in cybersecurity applications. Said Hoffman, “If we can’t answer the privacy question, we can’t put appropriate controls and protections in place.”

To discuss the implications of blurry privacy regulations, Dr. Manju Puri – J.B. Fuqua Professor of Finance at the Fuqua School of Business – discussed how the big data feeding modern AI algorithms impact each person’s digital footprint. Puri noted that data about a person’s phone usage patterns can be used by banks to decide whether that person should receive a loan. “People who call their mother every day tend to default less, and people who walk the same path every day tend to default less.” She contends that the biggest question is how to behave in a digital world where every action can be used against us.

Dr. Philip Napoli has observed behaviors in the digital world for several years as James R. Shepley Professor of Public Policy at the Sanford School, specifically focusing on self-reinforcing cycles of social media algorithms. He contends that Facebook’s algorithms, in particular, reward content that gets people angry, which motivates news organizations and political parties to post galvanizing content that will swoop through the feeds of millions. His work shows that AI algorithms can not only impact the behaviors of individuals, but also massive organizations.

At the end of the panel, there was one firm point of agreement between all speakers: AI is tremendously powerful. Hoffman even contended that there is a risk associated with not using artificial intelligence, which has proven to be a revolutionary tool in healthcare, finance, and security, among other fields. However, while proven to be immensely impactful, AI is not guaranteed to have a positive impact in all use cases – rather, as shown by failed image recognition platforms and racist healthcare algorithms that impacted millions of Black people, AI can be incredibly harmful.

Thus, while many in the AI community dream of a world where algorithms can be an unquestionable force for good, the underlying technology has a long way to go. What stands between the status quo and that idealistic future is not more data or more code, but less bias in data and code.

Post by Shariar Vaez-Ghaemi, Class of 2025


Decentralized Finance and the Power of Smart Contracts

Sticky post

When people use apps or services like Netflix, Instagram, Amazon, etc. they sign, or rather virtually accept, digital user agreements. Digital agreements have been around since the 1990s. These agreements are written and enforced by the institutions that create these services and products. However, in certain conditions, these systems fail and these digital or service-level agreements can be breached, causing people to feel robbed. 

A recent example of this is the Robinhood scandal that occurred in mid-2021. Essentially, people came together and all wanted to buy the same stock. However, Robinhood ended up restricting buying, citing issues with volatile stock and regulatory agreements. As a result, they ended up paying $70 million dollars in fines for system outages and misleading customers. And individual customers were left feeling robbed. This was partially the result of centralization and Robinhood having full control over the platform as well as enforcing the digital agreement.

Zak Ayesh Presenting on Chainlink
and Decentralized Smart Contracts

Zak Ayesh, a developer advocate at Chainlink recently came to Duke to talk about decentralized Smart Contracts that could solve many of the problems with current centralized digital agreements and traditional paper contracts as well. 

What makes smart contracts unique is that they programmatically implement a series of if-then rules without the need for a third-party human interaction. While currently these are primarily being used on blockchains, they were actually created by computer scientist Nick Szabo in 1994. Most smart contracts now run on blockchains because it allows them to remain decentralized and transparent. If unfamiliar with blockchain refer to my previous article here. 

Smart contracts are self-executing contracts with the terms of the agreement being directly written into computer code.

Zak Ayesh

There are several benefits to decentralized contracts. The first is transparency. Because every action on a blockchain is recorded and publicly available, the enforcement of smart contracts is unavoidably built-in. Next is trust minimization and guaranteed execution. With smart contracts, there is reduced counterparty risk — that’s the probability one party involved in a transaction or agreement might default on its contractual obligation because neither party has control of the agreement’s execution or enforcement. Lastly, they are more efficient due to automation. Operating on blockchains allows for cheaper and more frictionless transactions than traditional alternatives. For instance, the complexities of cross-border remittances involving multiple jurisdictions and sets of legal compliances can be simplified through coded automation in smart contracts.

Dr. Campbell Harvey, a J. Paul Sticht Professor of International Business at Fuqua, has done considerable research on smart contracts as well, culminating in the publication of a book, DeFi and the Future of Finance which was released in the fall of 2021.

In the book, Dr. Harvey explores the role smart contracts play in decentralized finance and how Ethereum and other smart contract platforms give rise to the ability for decentralized application or dApp. Additionally, smart contracts can only exist as long as the chain or platform they live on exists. However, because these platforms are decentralized, they remove the need for a third party to mediate the agreement. Harvey quickly realized how beneficial this could be in finance, specifically decentralized finance or DeFi where third-party companies, like banks, mediate agreements at a high price.  

“Because it costs no more at an organization level to provide services to a customer with $100 or $100 million in assets, DeFi proponents believe that all meaningful financial infrastructure will be replaced by smart contracts which can provide more value to a larger group of users,” Harvey explains in the book

Beyond improving efficiency, this also creates greater accessibility to financial services. Smart contracts provide a foundation for DeFi by eliminating the middleman through publicly traceable coded agreements. However, the transition will not be completely seamless and Harvey also investigates the risks associated with smart contracts and advancements that need to be made for them to be fully scalable.

Ultimately, there is a smart contract connectivity problem. Essentially, smart contracts are unable to connect with external systems, data feeds, application programming interfaces (APIs), existing payment systems, or any other off-chain resource on their own. This is something called the Oracle Problem which Chainlink is looking to solve.

Harvey explains that when a smart contract is facilitating an exchange between two tokens, it determines the price by comparing exchange rates with another similar contract on the same chain. The other smart contract is therefore acting as a price oracle, meaning it is providing external price information. However, there are many opportunities to exploit this such as purchasing large amounts on one oracle exchange in order to alter the price and then go on to purchase even more on a different exchange in the opposite direction. This allows for capitalization on price movement by manipulating the information the oracle communicates to other smart contracts or exchanges. 

That being said, smart contracts are being used heavily, and Pratt senior Manmit Singh has been developing them since his freshman year along with some of his peers in the Duke Blockchain Lab. One of his most exciting projects involved developing smart contracts for cryptocurrency-based energy trading on the Ethereum Virtual Machine allowing for a more seamless way to develop energy units.

One example of how this could be used outside of the crypto world is insurance. Currently, when people get into a car accident it takes months or even a year to evaluate the accident and release compensation. In the future, there could be sensors placed on cars connected to smart contracts that immediately evaluate the damage and payout.

Decentralization allows us to avoid using intermediaries and simply connect people to people or people to information as opposed to first connecting people to institutions that can then connect them to something else. This also allows for fault tolerance: if one blockchain goes down, the entire system does not go down with it. Additionally, because there is no central source controlling the system, it is very difficult to gain control of thus protecting against attack resistance and collusion resistance. While risks like the oracle problem need to be further explored, the world and importance of DeFi, as well as smart contracts, is only growing.

And as Ayesh put it, “This is the future.”

Post by Anna Gotskind, Class of 2022

What Happens When You Give People Money?

Paige Stampatori

What happens when you give people money? Dr. Aisha Nyandoro and Natalie Foster know: through their research, they’ve seen the impacts of guaranteed income firsthand.

On November 9, as part of the Duke Center for Child and Family Policy’s Sulzberger Distinguished Lecture series, these experts discussed their work and what we can learn from it at “What Happens When You Give People Money: The Future of Economic Security for Children and Families.”

Natalie Foster

Foster, co-founder and co-chair of the Economic Security Project, began with the big idea of guaranteed income. Before the pandemic, wealth and income inequality were at all-time highs — disparities that “can be traced back to the origins of racialized capitalism.” But recently, things have gotten even harder. Wages have remained stagnant despite increases in productivity — and despite inflation, making it harder to afford things like rent. Foster denounced the “strong ideology that says that lack of security in this system is a personal failing. That if you can’t pull yourself up, there’s something wrong with you.” There’s something wrong with the system, Foster said. “People are working. The economy isn’t.”

Foster explained that the 1996 “Personal Responsibility and Work Opportunity Reconciliation Act” fundamentally changed welfare by converting the old New Deal-era unlimited grant program into the flat-funded block grant we now know as TANF, leaving determination of eligibility to state discretion and generally “making welfare more punitive.” The Act, Foster said, was built on racist stereotypes, like that of the welfare queen. To make matters worse, it was passed against the backdrop of a persistent devaluation of the labor of people of color

Foster said that even though there didn’t appear to be room in these political conditions to do things differently, she had the “audacity to imagine something else: the ‘adjacent possible.’” She wanted to give cash to people directly, ensuring an income floor regardless of whatever crises that may abound.

Foster worked with the mayor of Stockton, California on the Stockton Economic Empowerment Demonstration (SEED), which provided 125 Stockton residents with $500 monthly payments for two years. 

Dr. Aisha Nyandoro

Foster was connected by a mutual friend to Nyandoro, the CEO of Springboard to Opportunities. Nyandoro had launched The Magnolia Mother’s Trust, which provides low-income Black mothers in Jackson, Mississippi with $1,000 monthly payments for one year. 

With The Magnolia Mother’s Trust, Nyandoro sought to shift away from economic policy “rooted in ‘what is,’ and toward ‘what could be.’” This concept has a rich history, she said, and includes the work of Martin Luther King Jr. and the Black Panthers. She had a specific ‘what if’ in mind: “What if when Black women told us what they needed, we believed them?” What if we sought to overturn the very structures that keep these people down, and subverted the “paternalistic nature of the social safety net”? 

Nyandoro stated that as a researcher, when she has questions, she “goes back to the people.” When she did, she found that although people’s needs were individual, “cash was ubiquitous” — cash was a solution that could address every single one of the problems that she heard. Giving cash directly could help combat a system that “penalizes people for being poor, rather than trying to lift them out of poverty.” 

Why low-income Black mothers? Nyandoro explained that in order to do the work of economic liberation, one must identify what’s wrong with the system. In this case, that meant identifying those who are the most negatively impacted by the system, and using what limited resources are available to help them specifically.

Nyandoro turned to her findings: giving people cash works. These mothers are often working tirelessly, holding down two or three jobs and struggling to make ends meet. After receiving the money, people continue to work and often do so at higher rates (a major fear of opponents of guaranteed income). As a result, their income is often doubled — with life-changing results

Beyond the numbers, Nyandoro emphasized that “we are seeing joy. We don’t talk about joy enough as it relates to Black women.” This money allowed Black women to feel free, to be entrepreneurial: to “dare to dream for the first time — for themselves and for their families.” 

She referenced Chimamanda Ngozi Adichie’s famous speech “The Danger of a Single Story,” explaining that in order to change the narrative, “we need to change the narrator.” It’s time to think about whose voices we center.

In Jackson, Mississippi and Stockton, California, the pair had carried out research about the ‘adjacent possible.’ They’d used cities and states as “laboratories in democracy.” Foster said that their work was paving the way for gradual advances in guaranteed income — slowly, but surely. Then, the pandemic hit.

Suddenly, ideas that had recently been dismissed as too radical were viewed as necessary. Often unable to work, people needed money fast in order to put food on the table and cover their most urgent needs. The federal government rose to the challenge with the American Rescue Plan, providing stimulus checks and pandemic unemployment insurance, plus expanding the Child Tax Credit. “The ‘adjacent possible’”, Foster said, “had become the possible.”

The country saw an “immediate drop in poverty.” The pandemic was revealing, said Foster. It revealed that cash provides time, stress reduction, and resilience. It revealed that cash serves as a tool to create economic security and “build back better.” Above all, it revealed that “poverty is a policy choice that we’re currently making. We could make a different policy choice in order to eliminate it.”

The pandemic also revealed that stimulus checks and the Child Tax Credit were “very popular policies.” Nyandoro has observed support in the form of petitions for monthly cash transfers, the founding of organizations like Mayors for a Guaranteed Income and Guaranteed Income Community of Practice, and the launch of over a hundred guaranteed income pilots of some sort. All these efforts, Nyandoro said, are pushing toward “the same North Star”: centering the needs of families and achieving economic liberation through federal policy.

Foster turned the discussion toward next steps: “these victories have been immense, but could disappear” if the Build Back Better Act does not pass. The Act includes a year-long extension of the expanded Child Tax Credit, a key instantiation of guaranteed income. The Child Tax Credit has bipartisan support

If the extension of the Child Tax Credit passes, then according to Foster, guaranteed income is one step closer to becoming a cornerstone of social policy. This would be a “nail in the coffin of the way we’ve done policy for the last fifty years — that you’re only worth what you do in the world. Every human has dignity and worth, and we have the opportunity to build a policy that says just that.” 

Nyandoro agreed with Foster. As an anti-poverty advocate, she believes in a world without poverty: a world where “everyone can have a life of dignity for themselves and their families.” She believes that the ‘adjacent possible’ is achievable if “we can move beyond our own individual needs in order to view life as a collective, where prosperity is shared rather than hoarded.” She ended by quoting Toni Morrison: “if you have some power, then your job is to empower someone else.”

Last Friday, the House voted to pass the Build Back Better Act, which now heads to the Senate.

Post by Zella Hanson

The Duke Blockchain Lab: Disrupting and Redefining Finance

The first decentralized cryptocurrency, Bitcoin, was created in 2009 by a developer named Satoshi Nakamoto which is assumed to be a pseudonym. Over the last decade, cryptocurrency has taken the world by storm, influencing the way people think about the intersection of society and economics. Cryptocurrencies like Bitcoin or Ethereum, another popular token, operate on blockchains.

Manmit Singh, a senior studying electrical and computer engineering, was introduced to blockchain his freshman year at Duke after meeting Joey Santoro ‘19, a senior studying computer science at the time.

Singh quickly found that he was not only interested in the promise of blockchain but skilled at building blockchain applications as well. As a result, he joined the Duke blockchain lab, a club on campus that, at the time, had no more than fifteen students. Singh, who is now president of the Duke Blockchain Lab, explained that there are now over 100 members in the club working on different projects related to blockchain. 

“Blockchain is a computer network with a built-in immutable ledge.”

Manmit SIngh

Essentially, computers process information, the internet allows us to communicate information and blockchain is the next step in the evolution of the digital era. It not only allows computers to communicate value but to transfer it as well in a completely transparent way because every transaction is tracked and, a record of that transaction is added to every participant’s ledger which is visible to others.

The concept and application of blockchain is not intuitive to everybody. Not only do people have difficulty understanding it, but they do not even know where to begin asking questions. 

For Singh, a key element to the club’s success was recruiting new members. The crypto space experienced a crash in 2017 resulting in a lot of skepticism around an already novel idea, decentralized currency. As a result, it was crucial to educate others on the potential of decentralized finance (DeFi), cryptocurrency, and, of course, blockchain. When recruiting, Singh wanted to bring in both tech and business-focused students so that they could not only work on building blockchain applications but conduct research on business models and how to generate value within decentralized finance as well.

Members of the Duke Blockchain Lab at a
weekly meeting learning about Stablecoins,
one type of token in cryptocurrency

Currently, members are working on a variety of projects including looking at consensus algorithms or how the blockchain makes decisions given that it is decentralized so inherently no one is in control. However, their most ambitious venture is the development of their Crypto Fund where people can invest money.

They are also looking to develop a Duke-inspired marketplace with talented Duke artists to sell non-fungible-tokens or NFTs. If unfamiliar, Abby Shlesinger, a senior studying Art History, created a blog to educate people on what NFTs are. 

One of the first projects Singh led involved developing a “smart contract” for cryptocurrency-based energy trading on the Ethereum Virtual Machine, a computation engine that acts like a decentralized computer that can hold millions of executable projects. Smart contracts are programs stored on a blockchain that run when predetermined conditions are met.

Additionally, Singh and other members of the Duke Blockchain Lab are working on tokenomic research with Dr. Harvey, a Duke professor who recently published a book alongside Santoro titled “DeFi and the Future of Finance” which you can find here. 

“Every blockchain is a complete economy that exists on a different plane.” 

Within these blockchain economies are various different types of tokens that vary in function and value. Tokenomics explores how these economies work and can be used to generate value. When asked to compare tokenomic concepts to ones in traditional finance, Singh explained that payment tokens are like dollars, asset tokens are like bonds and security tokens are like stocks. Currently, several companies are working on creating competitive blockchains that will be both cheaper and faster allowing creating an avenue for blockchain to continue accelerating into the mainstream. 

Meanwhile, Santoro, who introduced Singh to blockchain, graduated from Duke in 2019 and went on to form The Fei Protocol, a stable coin that unlike bitcoin does not change in value. His protocol raised one billion dollars within several weeks and while it had some initial challenges, it is now set to launch V2, a second version, soon. 

Singh plans to continue working on blockchain applications after graduating this spring and hopes to combine it with his passion for entrepreneurship.

“I am enthused by the applications of artificial intelligence, blockchain, and the internet of things in disrupting the world as we know it.”

Manmit Singh
By: Anna Gotskind

Back in Action: HackDuke’s 2021 “Code for Good”

If you walked across Duke’s Engineering Quad between 9AM on Saturday, October 23rd, and 5PM on Sunday, October 24th, the scene might’ve looked like that of any other day: students gathered in small groups, working diligently.

But then you’d see the giant banner and realize something special was afoot. These students were participating in HackDuke’s “Code for Good,” one of the most eminent social good hackathons in the country.

Participants have to “build something, not just an idea,” said Anita Li, co-director of HackDuke. Working in teams, students develop software, hardware, or quantum solutions to problems in one of four tracks: inequality, health, education, and energy and environment.

Participants can win “track prizes,” where $2,400 in total donations are made in winners’ names ($300 for first, $200 for second, $100 for third) to charities doing work in that track. There are other prizes too. Sponsors, including Capital One, Accenture, and Microsoft give incentives: if participants incorporate their technology or use their database, they’re qualified to win that sponsor’s prize (gift cards, usually, or software worth hundreds of dollars).

This year, Duke’s department of Student Affairs sponsored the health track, in hopes that participants might come up with ideas that could help promote student wellness here at Duke. “It’s a great space for thinking about these issues,” Li said.

Li told me they had more than 1,000 registrations, though there’s always a little less turnout. HackDuke is open to all students and recent graduates, so that “you get to see these cool ideas from everywhere.”

Just under half of this year’s participants were from Duke, almost 10% hailed from UNC, and the rest were from other universities across the US and the world. 30 percent of participants were women — a significant increase from the last HackDuke covered by the Research Blog, in 2014. 

This year is “particularly interesting,” Li said, because of the hybrid model. Last year, everything was virtual. This year, about 300 (vaccinated) students attended in person, making HackDuke one of the few Major League Hacking events with an in-person component this year. With the hybrid model, talks, workshops, and demos are all livestreamed so that no one misses out.

Some social events also had online elements: you could zoom into the Bob Ross painting session as well as the open mic, which Li said quickly turned into karaoke night. The spicy ramen challenge was “a little harder over Zoom.”

I came across Sydney Wang and Ray Lennon, along with teammate Jean Rabideau, as they were building a web app called JamJar for the Education Track contest. In the app, students give real-time feedback to teachers about how well they’re understanding the material. There are three categories: engagement (you can rank your engagement along a scale from “mentally I’m in outer space” to “locked in), understanding (“where am I?” to “crystal clear”), and speed (“a glacial pace” to “TOO FAST!”). Student responses get compiled and graphed to show mean markers of understanding over time. 

Lennon said he’s participating because “this is the best way to learn: to be thrown in the fire and have to learn as you go.” Wang felt the same way. She’s new to coding, and feels like she’s learning a lot from Lennon.

Like Lennon and Wang, many participants see HackDuke as an opportunity to learn. There are technical workshops where participants can learn HTML and CSS. There are talks where speakers discuss working in the coding and social good sector. The CTO of change.org, Elaine Zhou, flew to Durham to speak to participants about her experience. So there’s a networking opportunity, too — participants can meet people like Zhou doing the work they want to do, and professors and company representatives who can help them on their journey to get there.

There were challenges. Staying hydrated was one: by Sunday morning, they’d gone through seven cases of water, 16 cases of soda, and three cases of red bull. “It takes a lot of liquids,” Li said. And then there’s sleep — or lack thereof. When Li was participating in her freshman year, she slept for about three hours. Many people pull all-nighters, but “nap sporadically everywhere,” Li said. “It’s like finals season, with everyone knocked out.” She saw a handful of guys sleeping on the floor in Fitzpatrick. She gave them bed pads. 

Li’s love for HackDuke is contagious. She loves to see participants focusing on social good and drawing on their awareness of what’s happening in the world. “People are thinking about things that are intense; they’re really worrying about issues facing certain communities,” Li said.

At HackDuke, people really are coding for good.

Post by Zella Hanson

The Black Wealth Gap in Modern Day America

“White Americans have been provided with up escalators they can ride to reach their goals without hurdles. Meanwhile, Black Americans have been forced onto down escalators which they must run-up to reach their destination.”

The Samuel Dubois Cook Center on Social Equity at Duke University recently released a striking report on Black wealth in America, entitled “Still Running Up the Down Escalator: How Narratives Shape our Understanding of Racial Wealth Inequality,” This 36-page report, written by Natasha Hicks, Fenaba Addo, Anne Prince, and William Darity examines the stark inequalities in the economic situation of Black Americans.

The cover page of the 36-page, in-depth report, published earlier this fall.

“Despite a decade of philanthropic investment and renewed attention from progressive elected officials, policymakers, and advocates, we have yet to make discernible progress in ensuring Black families have the power and freedom wealth bestows,” the report says (page 1).

“The typical Black household’s wealth (in 2019) was $24,100; for White households, it was $188,200. This translates into the typical Black household holding about 12 cents for every dollar of wealth held by the typical White family– a disparity that has remained largely unchanged since 1989 (Kent and Ricketts, 2020).” ( page 6)

Black families are disproportionately shut out of access to opportunities that would improve generational wealth, such as home loans, business loans/ownership, and financial assets. Because of the long history of these inequalities, Black wealth in America has improved little in the last 10 years.

The report continues by analyzing how Covid-19, the worst Pandemic in US History, has widened the wealth gap in America.

“Racial wealth inequality remains a persistent defining American issue, particularly in the wake of the COVID-19 pandemic’s disproportionate toll on the physical and financial health of Black people,” the report says. “The COVID-19 pandemic and the corresponding economic crisis have only exacerbated what was already a collective failing by policymakers and elected officials, who continue to invest in solutions focused on individual behavior instead of systems change.”

Covid-19 placed over 114 million people into unemployment over the course of the pandemic, with an overrepresentation of Black Americans in these figures. The figures below were published in the report to highlight the number of liquid assets and wealth available to white families versus black families in 2019, just one year before the pandemic.

This figure taken from the report shows the median liquid assets by race and income. ( figure 1, page 8)
This figure taken from the report shows the median wealth accumulated by race and wealth quintiles. (figure 2, page 8)

As illustrated by these figures, the average White family in America maintains a leg up financially through both income and assets, which is why when the pandemic hit, black Americans were the ones disproportionately affected. Without access to high wealth modules or liquid assets to lean on, the economic wealth gap in America grew bigger.

The next part of the report talked about how false narratives in America regarding economic inequality is leading to unsuccessful aims of correction. In America, it’s a common theme to assume the problems faced by Black Americans are a cultural or personal issue, instead of a systemic one.

“Harmful narratives that characterize Black Americans as unintelligent, lazy, and criminal reinforce the notion that racial wealth disparities between Black and White households arise from differences in culture, values, skills, and behavior.” (page 10) Themes of anti-Blackness and personal responsibility, or a bootstrap mentality, were key systemic factors noted in the report. These factors impacted almost every aspect of Black America, including education, homeownership, entrepreneurship, family structure, and income and employment.

The report concludes by bringing up tangible solutions for these structural problems.

“The past year of crises is exposing the fact that we created systems, rules, and policies that actively and intentionally harm Black people. In order to truly address racial wealth inequality and the impact of the COVID-19 crisis, policymakers and funders must move away from solutions focused on behavioral changes and individual choices. Rather, they must take bold actions (backed by large scale financial investments) to shift dominant narratives and reimagine economic structures that support, uplift and protect Black people.” (page 23)

The authors make four broad proposals: shift harmful narratives, eliminate the racial wealth gap, dismantle extractive policies, and design programs to seed intergenerational wealth.

Economic disparities in America are a systemic issue, not a cultural or personal one. This report examines the interplay between this issue and the current pandemic, maintaining that the only way to create tangible change is through systemic solutions.

“America offers a false promise of equal opportunity and individual agency. For Black Americans, making all the right choices does not equal all the right outcomes. Just as wealth-building for White people in America was by design and government action, we need intentional and structural wealth-building strategies for Black Americans with investments compared to those given to White Americans. This requires a paradigm shift to truly tackle racial wealth inequality.” (page 36)

Written by Skylar Hughes, Class of 2025

Dr. Laura Richman is Defining Health by its Social Determinates

In 2010, the Affordable Care Act sparked a nationwide debate on the extent of responsibility the American government has over our healthcare. But Dr. Laura Richman has been asking that question since long before that. 

Richman is a health psychologist. “I examine psychosocial factors that have an impact on health behaviors and health outcomes,” she explains, sitting across from me at the Law School café. (Neither of us were wearing a cardigan. It was rather hot outside). 

Laura Richman Ph.D. is an associate professor in population health sciences. (image: Scholars@Duke)

Richman is an associate professor at Duke in the Population Health Sciences, an associate of the Duke Initiative for Science & Society, and, coincidentally, my professor in the Science & the Public FOCUS cluster. She co-teaches the course Science, Law, and Policy with Dr. Yousef Zafar, in which we examine the social determinants of health through the lens of cancer screening, diagnosis, and treatment.

After graduating from the University of Virginia in 1997 with a Ph.D. in social psychology, Richman worked at a sort of think-tank for health professionals collaborating on social issues. This inspired her to pursue health research through the lens of social determinants.

“There was a lot of work on substance use, on mental health, on behavioral disorders. That certainly contributed to my continued interest in factors that have an influence on these [health] outcomes,” she said. 

Continuing in this work, she became a research associate at the School of Public Health at Harvard University; Richman described her time at Harvard as “exciting,” which is not a word used by many to describe empirical research environments. “Certainly there’s that really robust relationship between low income, low education, low job status and poor health outcomes, but a lot of those pathways— like the ones we talk about in class, Olivia— had not been studied.” 

She’s referring to the public health concept of ‘upstream’ and ‘downstream’ solutions. (The river parable goes as follows: when you observe a trend in people drowning in a certain river, you are presented with different ways of solving the problem. You can start pulling people out of the river and saving them one at a time, which is called a “downstream” solution in public health. You can also prevent people from falling into the river, which is called an “upstream” solution.)

(courtesy of SaludAmerica!)

Richman’s professional research explores another crucial social determinant of health we discussed in class: perceived versus actual discrimination. She asked whether marginalization — objectively or subjectively — can affect functioning, “both psychologically and cognitively. Like, how does it affect their thought processes? Their decision-making? Then, how does that affect their health?” You can read her study here

One thing I noted immediately was Richman’s affinity for creative research design. In a lab she headed at Duke, she conducted one experiment with a student that tested the aforementioned effect of marginalization on health decisions. They provided subjects with a choice between unhealthy and healthy snack options after watching a video of, reading a passage about, or imagining members of their community experience discrimination.

In one study we read for Science, Law, and Policy, the stress effect of discrimination towards Arabic-named individuals after 9/11 was measured through the birth outcomes of Arabic-named mothers pregnant during that time. When I asked her about this, she said, “Particularly working with students, I think that they just bring so much energy and creativity to the research. Surveys serve their purpose — I think they’re really important, but I think there are just lots of opportunities to do more with research designs and research questions. I like trying to approach things from a different angle.” 

Richman is also working on a book. She is studying relational health — health as determined by the opioid epidemic, the obesity crisis, and social isolation associated with aging. She hopes her project will be used in classrooms (and by the interested layman), and that the value of social determinants of health is reflected in increased funding dollars, more people interested in health disparities, more focus in medical education on the screening and referral system, and stimulating dialogue among people in positions of power on a policy level.

Post by Olivia Ares, Class of 2025

New Blogger Shariar Vaez-Ghaemi: Arts and Artificial Intelligence

Hi! My name is Shariar. My friends usually pronounce that as Shaw-Ree-Awr, and my parents pronounce it as a Share-Ee-Awr, but feel free to mentally process my name as “Sher-Rye-Eer,” “Shor-yor-ior-ior-ior-ior,” or whatever phonetic concoction your heart desires. I always tell people that there’s no right way to interpret language, especially if you’re an AI (which you might be).

Speaking of AI, I’m excited to study statistics and mathematics at Duke! This dream was born out of my high school research internship with New York Times bestselling author Jonah Berger, through which I immersed myself in the applications of machine learning to the social sciences. Since Dr. Berger and I completed our ML-guided study of the social psychology of communicative language, I’ve injected statistical learning techniques into my investigations of political science, finance, and even fantasy football.

Unwinding in the orchestra room after a performance

When I’m not cramped behind a Jupyter Notebook or re-reading a particularly long research abstract for the fourth time, I’m often pursuing a completely different interest: the creative arts. I’m an orchestral clarinetist and quasi-jazz pianist by training, but my proudest artistic endeavours have involved cinema. During high school, I wrote and directed three short films, including a post-apocalyptic dystopian comedy and a silent rendition of the epic poem “Epopeya de la Gitana.”

I often get asked whether there’s any bridge between machine learning and the creative arts*, to which the answer is yes! In fact, as part of my entry project for Duke-based developer team Apollo Endeavours, I created a statistical language model that writes original poetry. Wandering
Mind, as I call the system, is just one example of the many ways that artificial intelligence can do what we once considered exclusively-human tasks. The program isn’t quite as talented as Frost or Dickinson, but it’s much better at writing poetry than I am.

In a movie production (I’m the one wearing a Totoro onesie)

I look forward to presenting invigorating research topics to blog readers for the next year or more. Though machine learning is my scientific expertise, my investigations could transcend all boundaries of discipline, so you may see me passionately explaining biology experiments, environmental studies, or even macroeconomic forecasts. Go Blue Devils!

(* In truth, I almost never get asked this question by real people unless I say, “You know, there’s actually a connection between machine learning and arts.”)

By Shariar Vaez-Ghaemi, Class of 2025

‘Anonymous Has Viewed Your Profile’: All Networks Lead to Re-Identification

For half an hour this rainy Wednesday, October 6th, I logged on to a LinkedIn Live series webinar with Dr. Jiaming Xu from the Fuqua School of Business. I sat inside the bridge between Perkins and Bostock, my laptop connected to DukeBlue wifi. I had Instagram open on my phone and was tapping through friends’ stories while I waited for the broadcast to start. I had Google Docs open in another tab to take notes. 

The title of the webinar was “Can Anyone Truly Be Anonymous Online?” 

Xu spoke about “network privacy,” which is “the intersection of network analysis and data privacy.” When you make an account, connect to wifi, share your location, search something online, or otherwise hint at your personal information, you are creating a “user profile”: a network of personal data that hints at your identity. 

You are probably familiar with how social media companies track your decisions to curate a more engaging experience for you (i.e. the reason I scroll through TikTok for 5 minutes, then 30 minutes, then… Oh no! Two hours have gone by). Other companies track other kinds of data— data that isn’t always just for algorithmic manipulation or creepy-accurate Amazon ads (i.e. “Hey! I was just thinking about buying cat litter. How did Mr. Bezos know?”). Your name, work history, date of birth, address, location, and other critical identifying factors can be collected even if you think your profile is scrubbed clean. In a rather on-the-nose anecdote to his LinkedIn audience on Wednesday, Xu explained that in April 2021, over 500 million user profiles on LinkedIn were hacked. Valuable, “sensitive, work-related data,” he noted, was made vulnerable. 

Image courtesy of Flickr

So, what do you have to worry about? I know I tend to not worry about my personal information online; letting companies collect my data benefits me. I can get targeted Google ads about things I’m interested in and cool filters on Snapchat. In a medical setting, Xu said, prediction algorithms may help patients’ health in the long run. But even anonymized and sanitized data can be traced back to you. For further reading: in an essay published in July 2021, philosophers Evan Selinger and Judy Rhee elaborate on the dangers of “normalizing surveillance.”

The meat of Xu’s talk was how your data can be traced back to you. Xu gave three examples. 

The first was a study conducted by researchers at the University of Texas- Austin attempting to identify users submitting “anonymous” reviews for movies on Netflix (keep in mind this was 2007, so picture the red Netflix logo on the DVD box accordingly). To achieve this, they cross-referenced the network of reviews published by Netflix with the network of individuals signed up on IMDB; they matched those who reviewed movies similarly on both platforms with their public profiles on IMDB. You can read more about that specific study here. (For those unafraid of the full research paper, click here). 

Let’s take a pause to learn a new vocab word! “Signatures.” In this example, the signature was users’ movie ratings. See if you can name the signature in the other two examples.

The second example was conducted by the same researchers; to identify users on Twitter who shared their data anonymously, it was simply a matter of cross-referencing the network of Twitter users with Flickr users. If you know a guy who knows a guy who knows a guy who knows a guy, you and that group of people are likely to initiate that same chain of following each other on every social media platform you have (it may remind you of the theory that you are connected by “six degrees of separation” from every person on the planet, which, as it turns out, is also supported by social media data). The researchers were able to identify the correct users 30.8% of the time. 

Time for another vocab break! Those users who connect groups of people who know a guy who know a guy who know a guy are called “seeds.” Speaking of which, did you identify the signature in this example? 

Image courtesy of Flickr

The third and final example was my personal favorite because it was the funkiest and creative. Facebook user data— also “scrubbed clean” before being sold to third-party advertisers— was overlain with LinkedIn user data to reveal a network of connections that are repeated. How did they match up those networks, you ask? First, the algorithm assigned a computed score to every individual user based on how many Facebook friends they have and one for every user based on how many LinkedIn connections they have. Then, each user was assigned a list of integers based on their friends’ popularity score. Bet you weren’t expecting that. 

This method sort of improves upon the Twitter/Flickr example, but in addition to overlaying networks and chains of users, it better matches who is who. Since you are likely to know a guy who knows a guy who knows a guy, but you are also likely to know all of those guys down the line, following specific chains does not always accurately convey who is who. Unlike the seeds signature, the friends’ popularity signature was able to correctly re-identify users most of the time. 

Sitting in the bridge Wednesday, I was connected to many networks that I wouldn’t think could be used to identify me through my limited public data. Now, I’m not so sure.

So, what’s the lesson here? At the least, it was fun to learn about, even if the ultimate realization leaves us powerless against big data analytics. Your data has monetary value, and it is not as secure as you think: but it may be worth asking whether or not we even have the ability to protect our anonymity.

A New Algorithm for “In-Betweening” images applied to Covid, Aging and Continental Drift

Collaborating with a colleague in Shanghai, we recently published an article that explains the mathematical concept of ‘in-betweening,’in images – calculating intermediate stages of changes in appearance from one image to the next.

Our equilibrium-driven deformation algorithm (EDDA) was used to demonstrate three difficult tasks of ‘in-betweening’ images: Facial aging, coronavirus spread in the lungs, and continental drift.

Part I. Understanding Pneumonia Invasion and Retreat in COVID-19

The pandemic has influenced the entire world and taken away nearly 3 million lives to date. If a person were unlucky enough to contract the virus and COVID-19, one way to diagnose them is to carry out CT scans of their lungs to visualize the damage caused by pneumonia.

However, it is impossible to monitor the patient all the time using CT scans. Thus, the invading process is usually invisible for doctors and researchers.

To solve this difficulty, we developed a mathematical algorithm which relies on only two CT scans to simulate the pneumonia invasion process caused by COVID-19.

We compared a series of CT scans of a Chinese patient taken at different times. This patient had severe pneumonia caused by COVID-19 but recovered after a successful treatment. Our simulation clearly revealed the pneumonia invasion process in the patient’s lungs and the fading away process after the treatment.

Our simulation results also identify several significant areas in which the patient’s lungs are more vulnerable to the virus and other areas in which the lungs have better response to the treatment. Those areas were perfectly consistent with the medical analysis based on this patient’s actual, real-time CT scan images. The consistency of our results indicates the value of the method.

The COVID-19 pneumonia invading (upper panel) and fading away (lower panel) process from the data-driven simulations. Red circles indicate four significant areas in which the patient’s lungs were more vulnerable to the pneumonia and blue circles indicate two significant areas in which the patient’s lungs had better response to the treatment. (Image credit: Gao et al., 2021)
We also applied this algorithm to simulate human facial changes over time, in which the aging processes for different parts of a woman’s face were automatically created by the algorithm with high resolution. (Image credit: Gao et al., 2021. Video)

Part II. Solving the Puzzle of Continental Drift

It has always been mysterious how the continents we know evolved and formed from the ancient single supercontinent, Pangaea. But then German polar researcher Alfred Wegener proposed the continental drift hypothesis in the early 20th century. Although many geologists argued about his hypothesis initially, more sound evidence such as continental structures, fossils and the magnetic polarity of rocks has supported Wegener’s proposition.

Our data-driven algorithm has been applied to simulate the possible evolution process of continents from Pangaea period.

The underlying forces driving continental drift were determined by the equilibrium status of the continents on the current planet. In order to describe the edges that divide the land to create oceans, we proposed a delicate thresholding scheme.

The formation and deformation for different continents is clearly revealed in our simulation. For example, the ‘drift’ of the Antarctic continent from Africa can be seen happening. This exciting simulation presents a quick and obvious way for geologists to establish more possible lines of inquiry about how continents can drift from one status to another, just based on the initial and equilibrium continental status. Combined with other technological advances, this data-driven method may provide a path to solve Wegener’s puzzle of continental drift.

The theory of continental drift reconciled similar fossil plants and animals now found on widely separated continents. The southern part after Pangaea breaks (Gondwana) is shown here evidence of Wegener’s theory. (Image credit: United States Geological Survey)
The continental drift process of the data-driven simulations. Black arrow indicates the formation of the Antarctic. (Image credit: Gao et al., 2021)

The study was supported by the Department of Mathematics and Physics, Duke University.

CITATION: “Inbetweening auto-animation via Fokker-Planck dynamics and thresholding,” Yuan Gao, Guangzhen Jin & Jian-Guo Liu. Inverse Problems and Imaging, February, 2021, DOI: 10.3934/ipi.2021016. Online: http://www.aimsciences.org/article/doi/10.3934/ipi.2021016

Yuan Gao

Yuan Gao is the William W. Elliot Assistant Research Professor in the department of mathematics, Trinity College of Arts & Sciences.

Jian-Guo Liu is a Professor in the departments of mathematics and physics, Trinity College of Arts & Sciences.

Jian-Guo Liu

Page 1 of 9

Powered by WordPress & Theme by Anders Norén