Stefaan Verhulst
About: “…The newly founded Global AI Ethics Consortium (GAIEC) on Ethics and the Use of Data and Artificial Intelligence in the Fight Against COVID-19 and other Pandemics aims to:
- Support immediate needs for expertise related to the COVID-19 crisis and the emerging ethical questions related to the use of AI in managing the pandemic.
- Create a repository that includes avenues of communication for sharing and disseminating current research, new research opportunities, and past research findings.
- Coordinate internal funding and research initiatives to allow for maximum opportunities to pursue vital research related to health crises and the ethical use of AI.
- Discuss research findings and opportunities for new areas of collaboration.
Read the Statement of Purpose and find out more about the Global AI Ethics Consortium and its founding members: Christoph Lütge (TUM Institute for Ethics in Artificial Intelligence, Technical University of Munich), Jean-Gabriel Ganascia (LIP6-CNRS, Sorbonne Université), Mark Findlay (Centre for AI and Data Governance, Law School, Singapore Management University), Ken Ito and Kan Hiroshi Suzuki (The University of Tokyo), Jeannie Marie Paterson (Centre for AI and Digital Ethics, University of Melbourne), Huw Price (Leverhulme Centre for the Future of Intelligence, University of Cambridge), Stefaan G. Verhulst (The GovLab, New York University), Yi Zeng (Research Center for AI Ethics and Safety, Beijing Academy of Artificial Intelligence), and Adrian Weller (The Allan Turing Institute).
If you or your organization is interested in the GAIEC — Global AI Ethics Consortium please contact us at ieai@mcts.tum.de…(More)”.
Data Collaborative Case Study by Michelle Winowatan, Andrew Young, and Stefaan Verhulst: “The Atlas of Inequality is a research initiative led by scientists at the MIT Media Lab and Universidad Carlos III de Madrid. It is a project within the larger Human Dynamics research initiative at the MIT Media Lab, which investigates how computational social science can improve society, government, and companies. Using multiple big data sources, MIT Media Lab researchers seek to understand how people move in urban spaces and how that movement influences or is influenced by income. Among the datasets used in this initiative was location data provided by Cuebiq, through its Data for Good initiative. Cuebiq offers location-intelligence services to approved research and nonprofit organizations seeking to address public problems. To date, the Atlas has published maps of inequality in eleven cities in the United States. Through the Atlas, the researchers hope to raise public awareness about segregation of social mobility in United States cities resulting from economic inequality and support evidence-based policymaking to address the issue.
Data Collaborative Model: Based on the typology of data collaborative practice areas developed by The GovLab, the use of Cuebiq’s location data by MIT Media Lab researchers for the Atlas of Inequality initiative is an example of the research and analysis partnership model of data collaboration, specifically a data transfer approach. In this approach, companies provide data to partners for analysis, sometimes under the banner of “data philanthropy.” Access to data remains highly restrictive, with only specific partners able to analyze the assets provided. Approved uses are also determined in a somewhat cooperative manner, often with some agreement outlining how and why parties requesting access to data will put it to use….(More)”.
MIT Sloan: “On February 19 in the Ukrainian town of Novi Sanzhary, alarm went up regarding the new coronavirus and COVID-19, the disease it causes. “50 infected people from China are being brought to our sanitarium,” began a widely read post on the messaging app Viber. “We can’t afford to let them destroy our population, we must prevent countless deaths. People, rise up. We all have children!!!”
Soon after came another message: “if we sleep this night, then we will wake up dead.”
Citizens mobilized. Roads were barricaded. Tensions escalated. Riots broke out, ultimately injuring nine police officers and leading to the arrests of 24 people. Later, word emerged that the news was false.
As the director-general of the World Health Organization recently put it, “we’re not just fighting an epidemic; we’re fighting an infodemic.”
Now a new study suggests that an “accuracy nudge” from social media networks could curtail the spread of misinformation about COVID-19. The working paper, from researchers at MIT Sloan and the University of Regina, examines how and why misinformation about COVID-19 spreads on social media. The researchers also examine a simple intervention that could slow this spread. (The paper builds on prior work about how misinformation diffuses online.)…(More)”.
Paper by Bapon Fakhruddin: “…A wide range of approaches could be applied to understand transmission, outbreak assessment, risk communication, cascading impacts assessment on essential and other services. The network-based modelling of System of Systems (SOS), mobile technology, frequentist statistics and maximum-likelihood estimation, interactive data visualization, geostatistics, graph theory, Bayesian statistics, mathematical modelling, evidence synthesis approaches and complex thinking frameworks for systems interactions on COVID-19 impacts could be utilized. An example of tools and technologies that could be utilized to act decisively and early to prevent the further spread or quickly suppress the transmission of COVID-19, strengthen the resilience of health systems and save lives and urgent support to developing countries with businesses and corporations are shown in Figure 2. There are also WHO guidance on ‘Health Emergency and Disaster Risk Management[8]’, UNDRR supported ‘Public Health Scorecard Addendum[9]’, and other guidelines (e.g. WHO practical considerations and recommendations for religious leaders and faith-based communities in the context of COVID-19[10]) that could enhance pandemic response plan. It needs to be ensured that any such use is proportionate, specific and protected and does not increase civil liberties’ risk. It is essential therefore to examine in detail the challenge of maximising data use in emergency situations, while ensuring it is task-limited, proportionate and respectful of necessary protections and limitations. This is a complex task and the COVID-19 wil provide us with important test cases. It is also important that data is interpreted accurately. Otherwise, misinterpretations could lead each sector down to incorrect paths.
Many countries are still learning how to make use of data for their decision making in this critical time. The COVID-19 pandemic will provide important lessons on the need for cross-domain research and on how, in such emergencies, to balance the use of technological opportunities and data to counter pandemics against fundamental protections….(More)”.
Essay by Erik Angner: “Ignorance,” wrote Charles Darwin in 1871, “more frequently begets confidence than does knowledge.”
Darwin’s insight is worth keeping in mind when dealing with the current coronavirus crisis. That includes those of us who are behavioral scientists. Overconfidence—and a lack of epistemic humility more broadly—can cause real harm.
In the middle of a pandemic, knowledge is in short supply. We don’t know how many people are infected, or how many people will be. We have much to learn about how to treat the people who are sick—and how to help prevent infection in those who aren’t. There’s reasonable disagreement on the best policies to pursue, whether about health care, economics, or supply distribution. Although scientists worldwide are working hard and in concert to address these questions, final answers are some ways away.
Another thing that’s in short supply is the realization of how little we know. Even a quick glance at social or traditional media will reveal many people who express themselves with way more confidence than they should…
Frequent expressions of supreme confidence might seem odd in light of our obvious and inevitable ignorance about a new threat. The thing about overconfidence, though, is that it afflicts most of us much of the time. That’s according to cognitive psychologists, who’ve studied the phenomenon systematically for half a century. Overconfidence has been called “the mother of all psychological biases.” The research has led to findings that are at the same time hilarious and depressing. In one classic study, for example, 93 percent of U.S. drivers claimed to be more skillful than the median—which is not possible.
“But surely,” you might object, “overconfidence is only for amateurs—experts would not behave like this.” Sadly, being an expert in some domain does not protect against overconfidence. Some research suggests that the more knowledgeable are more prone to overconfidence. In a famous study of clinical psychologists and psychology students, researchers asked a series of questions about a real person described in psychological literature. As the participants received more and more information about the case, their confidence in their judgment grew—but the quality of their judgment did not. And psychologists with a Ph.D. did no better than the students….(More)”.
Paper by Mirco Nanni: “The rapid dynamics of COVID-19 calls for quick and effective tracking of virus transmission chains and early detection of outbreaks, especially in the phase 2 of the pandemic, when lockdown and other restriction measures are progressively withdrawn, in order to avoid or minimize contagion resurgence. For this purpose, contact-tracing apps are being proposed for large scale adoption by many countries. A centralized approach, where data sensed by the app are all sent to a nation-wide server, raises concerns about citizens’ privacy and needlessly strong digital surveillance, thus alerting us to the need to minimize personal data collection and avoiding location tracking.
We advocate the conceptual advantage of a decentralized approach, where both contact and location data are collected exclusively in individual citizens’ “personal data stores”, to be shared separately and selectively, voluntarily, only when the citizen has tested positive for COVID-19, and with a privacy preserving level of granularity.
This approach better protects the personal sphere of citizens and affords multiple benefits: it allows for detailed information gathering for infected people in a privacy-preserving fashion; and, in turn this enables both contact tracing, and, the early detection of outbreak hotspots on more finely-granulated geographic scale. Our recommendation is two-fold. First to extend existing decentralized architectures with a light touch, in order to manage the collection of location data locally on the device, and allow the user to share spatio-temporal aggregates – if and when they want, for specific aims – with health authorities, for instance. Second, we favour a longer-term pursuit of realizing a Personal Data Store vision, giving users the opportunity to contribute to collective good in the measure they want, enhancing self-awareness, and cultivating collective efforts for rebuilding society….(More)”
Paper by Cass Sunstein: “Many incentives are monetary, and when private or public institutions seek to change behavior, it is natural to change monetary incentives. But many other incentives are a product of social meanings, about which people may not much deliberate, but which can operate as subsidies or as taxes. In some times and places, for example the social meaning of smoking has been positive, increasing the incentive to smoke; in other times and places, it has been negative, and thus served to reduce smoking.
With respect to safety and health, social meanings change radically over time, and they can be dramatically different in one place from what they are in another. Often people live in accordance with meanings that they deplore, or at least wish were otherwise. But it is exceptionally difficult for individuals to alter meanings on their own. Alteration of meanings can come from law, which may, through a mandate, transform the meaning of action into a bland, “I comply with law,” or into a less bland, “I am a good citizen.” Alteration of social meanings can also come from large-scale private action, engineered or promoted by “meaning entrepreneurs,” who can turn the meaning of action from, “I am an oddball,” to, “I do my civic duty,” or, “I protect others from harm.” Sometimes subgroups rebel against new or altered meanings, produced by law or meaning entrepreneurs, but often those meanings stick and produce significant change….(More)”.
Paper by Victoria Perez and Justin M. Ross: “Networks of overlapping local governments are the front line of governmental responses to pandemics. Local governments, both general purpose (municipalities, counties, etc.) and special districts (school, fire, police, hospital, etc.), implement state and federal directives while acting as a producer and as a third-party payer in the healthcare system. They possess local information necessary in determining the best use of finite resources and available assets. Furthermore, a liberal society requires voluntary cooperation of citizens skeptical of opportunistic authoritarianism. Therefore, successful local governance instills a reassuring division of political power.
The COVID-19 pandemic has created two significant challenges for local governments in their efforts to respond effectively to the crisis: public finance and intergovernmental collaboration. This brief recommends practical solutions to meet these challenges….(More)”.
Essay by Frank D. LoMonte at the Journal of Civic Information: “In an April 1 interview with NPR’s “Morning Edition,” retired U.S. Army Gen. Stanley A. McChrystal, former commander of U.S. forces in Iraq, explained that, in a crisis situation, accurate information from government authorities can be crucial in reassuring the public – and in the absence of accurate information, speculation and rumor will proliferate. Joni Mitchell, who’s probably never before appeared in the same paragraph with Stanley McChrystal, might have put it a touch more poetically: “Don’t it always seem to go; That you don’t know what you’ve got ’til it’s gone.”
The outbreak of the coronavirus strain COVID-19, which prompted the U.S. Department of Health and Human Services to declare a public health emergency on Jan. 31, 2020,3 is introducing Americans to a newfound world of austerity and loss. Professional haircuts, sit-down restaurant meals and recreational plane flights increasingly seem like memories from a bygone golden age (small inconveniences, to be sure, alongside the suffering of thousands who’ve died and the families they’ve left behind).
Access to information from government agencies, too, is adapting to a mail-order, drive-through society. As public-health authorities reached consensus that the spread of COVID-19 could be contained only by eliminating non-essential travel and group gatherings, strict adherence to open-meeting and public-records laws became a casualty alongside salad bars and theme-park rides. Governors and legislatures relaxed, or entirely waived, compliance with statutes that require agencies to open their meetings to in-person public attendance and promptly fulfill requests for documents.
As with all other areas of public life, some sacrifices in open-government formalities are unavoidable. With agencies down to a sustenance-level crew of essential workers, it’s unrealistic to expect that decades-old paper documents will be speedily located and produced. And it’s unsafe to invite people to congregate at public hearings to address their elected officials. But the public shouldn’t be alone in the sacrifice….(More)”.
Karen Hao at MIT Technology Review: “When it comes to predicting the spread of an infectious disease, it’s crucial to understand what Ryan Tibshirani, an associate professor at Carnegie Mellon University, calls the “the pyramid of severity.” The bottom of the pyramid is asymptomatic carriers (those who have the infection but feel fine); the next level is symptomatic carriers (those who are feeling ill); then come hospitalizations, critical hospitalizations, and finally deaths.
Every level of the pyramid has a clear relationship to the next: “For example, sadly, it’s pretty predictable how many people will die once you know how many people are under critical care,” says Tibshirani, who is part of CMU’s Delphi research group, one of the best flu-forecasting teams in the US. The goal, therefore, is to have a clear measure of the lower levels of the pyramid, as the foundation for forecasting the higher ones.
But in the US, building such a model is a Herculean task. A lack of testing makes it impossible to assess the number of asymptomatic carriers. The results also don’t accurately reflect how many symptomatic carriers there are. Different counties have different testing requirements—some choosing only to test patients who require hospitalization. Test results also often take upwards of a week to return.
The remaining option is to measure symptomatic carriers through a large-scale, self-reported survey. But such an initiative won’t work unless it covers a big enough cross section of the entire population. Now the Delphi group, which has been working with the Centers for Disease Control and Prevention to help it coordinate the national pandemic response, has turned to the largest platforms in the US: Facebook and Google.
In a new partnership with Delphi, both tech giants have agreed to help gather data from those who voluntarily choose to report whether they’re experiencing covid-like symptoms. Facebook will target a fraction of their US users with a CMU-run survey, while Google has thus far been using its Opinion Rewards app, which lets users respond to questions for app store credit. The hope is this new information will allow the lab to produce county-by-county projections that will help policymakers allocate resources more effectively.
Neither company will ever actually see the survey results; they’re merely pointing users to the questions administered and processed by the lab. The lab will also never share any of the raw data back to either company. Still, the agreements represent a major deviation from typical data-sharing practices, which could raise privacy concerns. “If this wasn’t a pandemic, I don’t know that companies would want to take the risk of being associated with or asking directly for such a personal piece of information as health,” Tibshirani says.
Without such cooperation, the researchers would’ve been hard pressed to find the data anywhere else. Several other apps allow users to self-report symptoms, including a popular one in the UK known as the Covid Symptom Tracker that has been downloaded over 1.5 million times. But none of them offer the same systematic and expansive coverage as a Facebook or Google-administered survey, says Tibshirani. He hopes the project will collect millions of responses each week….(More)”.