Paper by Julian House, Nicola Lacetera, Mario Macis & Nina Mazar: “We conducted a randomized controlled trial involving nearly 700 customer-service representatives (CSRs) in a Canadian government service agency to study whether providing CSRs with performance feedback with or without peer comparison affected their subsequent organ donor registration rates. Despite having no tie to remuneration or promotion, the provision of individual performance feedback three times over one year resulted in a 25% increase in daily signups, compared to otherwise similar encouragement and reminders. Adding benchmark information that compared CSRs performance to average and top peer performance did not further enhance this effect. Registrations increased more among CSRs whose performance was already above average, and there was no negative effect on lower-performing CSRs. A post-intervention survey showed that CSRs found the information included in the treatments helpful and encouraging. However, performance feedback without benchmark information increased perceived pressure to perform…(More)”.
Can Smartphones Help Predict Suicide?
Ellen Barry in The New York Times: “In March, Katelin Cruz left her latest psychiatric hospitalization with a familiar mix of feelings. She was, on the one hand, relieved to leave the ward, where aides took away her shoelaces and sometimes followed her into the shower to ensure that she would not harm herself.
But her life on the outside was as unsettled as ever, she said in an interview, with a stack of unpaid bills and no permanent home. It was easy to slide back into suicidal thoughts. For fragile patients, the weeks after discharge from a psychiatric facility are a notoriously difficult period, with a suicide rate around 15 times the national rate, according to one study.
This time, however, Ms. Cruz, 29, left the hospital as part of a vast research project which attempts to use advances in artificial intelligence to do something that has eluded psychiatrists for centuries: to predict who is likely to attempt suicide and when that person is likely to attempt it, and then, to intervene.
On her wrist, she wore a Fitbit programmed to track her sleep and physical activity. On her smartphone, an app was collecting data about her moods, her movement and her social interactions. Each device was providing a continuous stream of information to a team of researchers on the 12th floor of the William James Building, which houses Harvard’s psychology department.
In the field of mental health, few new areas generate as much excitement as machine learning, which uses computer algorithms to better predict human behavior. There is, at the same time, exploding interest in biosensors that can track a person’s mood in real time, factoring in music choices, social media posts, facial expression and vocal expression.
Matthew K. Nock, a Harvard psychologist who is one of the nation’s top suicide researchers, hopes to knit these technologies together into a kind of early-warning system that could be used when an at-risk patient is released from the hospital…(More)”.
Hurricane Ian Destroyed Their Homes. Algorithms Sent Them Money
Article by Chris Stokel-Walker: “The algorithms that power Skai’s damage assessments are trained by manually labeling satellite images of a couple of hundred buildings in a disaster-struck area that are known to have been damaged. The software can then, at speed, detect damaged buildings across the whole affected area. A research paper on the underlying technology presented at a 2020 academic workshop on AI for disaster response claimed the auto-generated damage assessments match those of human experts with between 85 and 98 percent accuracy.
In Florida this month, GiveDirectly sent its push notification offering $700 to any user of the Providers app with a registered address in neighborhoods of Collier, Charlotte, and Lee Counties where Google’s AI system deemed more than 50 percent of buildings had been damaged. So far, 900 people have taken up the offer, and half of those have been paid. If every recipient takes up GiveDirectly’s offer, the organization will pay out $2.4 million in direct financial aid.
Some may be skeptical of automated disaster response. But in the chaos after an event like a hurricane making landfall, the conventional, human response can be far from perfect. Diaz points to an analysis GiveDirectly conducted looking at their work after Hurricane Harvey, which hit Texas and Louisiana in 2017, before the project with Google. Two out of the three areas that were most damaged and economically depressed were initially overlooked. A data-driven approach is “much better than what we’ll have from boots on the ground and word of mouth,” Diaz says.
GiveDirectly and Google’s hands-off, algorithm-led approach to aid distribution has been welcomed by some disaster assistance experts—with caveats. Reem Talhouk, a research fellow at Northumbria University’s School of Design and Centre for International Development in the UK, says that the system appears to offer a more efficient way of delivering aid. And it protects the dignity of recipients, who don’t have to queue up for handouts in public…(More)”.
Is This the Beginning of the End of the Internet?
Article by Charlie Warzel: “…occasionally, something happens that is so blatantly and obviously misguided that trying to explain it rationally makes you sound ridiculous. Such is the case with the Fifth Circuit Court of Appeals’s recent ruling in NetChoice v. Paxton. Earlier this month, the court upheld a preposterous Texas law stating that online platforms with more than 50 million monthly active users in the United States no longer have First Amendment rights regarding their editorial decisions. Put another way, the law tells big social-media companies that they can’t moderate the content on their platforms. YouTube purging terrorist-recruitment videos? Illegal. Twitter removing a violent cell of neo-Nazis harassing people with death threats? Sorry, that’s censorship, according to Andy Oldham, a judge of the United States Court of Appeals and the former general counsel to Texas Governor Greg Abbott.
A state compelling social-media companies to host all user content without restrictions isn’t merely, as the First Amendment litigation lawyer Ken White put it on Twitter, “the most angrily incoherent First Amendment decision I think I’ve ever read.” It’s also the type of ruling that threatens to blow up the architecture of the internet. To understand why requires some expertise in First Amendment law and content-moderation policy, and a grounding in what makes the internet a truly transformational technology. So I called up some legal and tech-policy experts and asked them to explain the Fifth Circuit ruling—and its consequences—to me as if I were a precocious 5-year-old with a strange interest in jurisprudence…(More)”
The European Union-U.S. Data Privacy Framework
White House Fact Sheet: “Today, President Biden signed an Executive Order on Enhancing Safeguards for United States Signals Intelligence Activities (E.O.) directing the steps that the United States will take to implement the U.S. commitments under the European Union-U.S. Data Privacy Framework (EU-U.S. DPF) announced by President Biden and European Commission President von der Leyen in March of 2022.
Transatlantic data flows are critical to enabling the $7.1 trillion EU-U.S. economic relationship. The EU-U.S. DPF will restore an important legal basis for transatlantic data flows by addressing concerns that the Court of Justice of the European Union raised in striking down the prior EU-U.S. Privacy Shield framework as a valid data transfer mechanism under EU law.
The Executive Order bolsters an already rigorous array of privacy and civil liberties safeguards for U.S. signals intelligence activities. It also creates an independent and binding mechanism enabling individuals in qualifying states and regional economic integration organizations, as designated under the E.O., to seek redress if they believe their personal data was collected through U.S. signals intelligence in a manner that violated applicable U.S. law.
U.S. and EU companies large and small across all sectors of the economy rely upon cross-border data flows to participate in the digital economy and expand economic opportunities. The EU-U.S. DPF represents the culmination of a joint effort by the United States and the European Commission to restore trust and stability to transatlantic data flows and reflects the strength of the enduring EU-U.S. relationship based on our shared values…(More)”.
Call it data liberation day: Patients can now access all their health records digitally
Article by Casey Ross: “The American Revolution had July 4. The allies had D-Day. And now U.S. patients, held down for decades by information hoarders, can rally around a new turning point, October 6, 2022 — the day they got their health data back.
Under federal rules taking effect Thursday, health care organizations must give patients unfettered access to their full health records in digital format. No more long delays. No more fax machines. No more exorbitant charges for printed pages.
Just the data, please — now…The new federal rules — passed under the 21st Century Cures Act — are designed to shift the balance of power to ensure that patients can not only get their data, but also choose who else to share it with. It is the jumping-off point for a patient-mediated data economy that lets consumers in health care benefit from the fluidity they’ve had for decades in banking: they can move their information easily and electronically, and link their accounts to new services and software applications.
“To think that we actually have greater transparency about our personal finances than about our own health is quite an indictment,” said Isaac Kohane, a professor of biomedical informatics at Harvard Medical School. “This will go some distance toward reversing that.”
Even with the rules now in place, health data experts said change will not be fast or easy. Providers and other data holders — who have dug in their heels at every step — can still withhold information under certain exceptions. And many questions remain about protocols for sharing digital records, how to verify access rights, and even what it means to give patients all their data. Does that extend to every measurement in the ICU? Every log entry? Every email? And how will it all get standardized?…(More)”
Blueprint for an AI Bill of Rights
The White House: “…To advance President Biden’s vision, the White House Office of Science and Technology Policy has identified five principles that should guide the design, use, and deployment of automated systems to protect the American public in the age of artificial intelligence. The Blueprint for an AI Bill of Rights is a guide for a society that protects all people from these threats—and uses technologies in ways that reinforce our highest values. Responding to the experiences of the American public, and informed by insights from researchers, technologists, advocates, journalists, and policymakers, this framework is accompanied by From Principles to Practice—a handbook for anyone seeking to incorporate these protections into policy and practice, including detailed steps toward actualizing these principles in the technological design process. These principles help provide guidance whenever automated systems can meaningfully impact the public’s rights, opportunities, or access to critical needs.
- Safe and Effective Systems
- Data Privacy
- Notice and Explanation
- Algorithmic Discrimination Protections
- Human Alternatives, Consideration, and Fallback…(More)”.
Big Data and Official Statistics
Paper by Katharine G. Abraham: “The infrastructure and methods for developed countries’ economic statistics, largely established in the mid-20th century, rest almost entirely on survey and administrative data. The increasing difficulty of obtaining survey responses threatens the sustainability of this model. Meanwhile, users of economic data are demanding ever more timely and granular information. “Big data” originally created for other purposes offer the promise of new approaches to the compilation of economic data. Drawing primarily on the U.S. experience, the paper considers the challenges to incorporating big data into the ongoing production of official economic statistics and provides examples of progress towards that goal to date. Beyond their value for the routine production of a standard set of official statistics, new sources of data create opportunities to respond more nimbly to emerging needs for information. The concluding section of the paper argues that national statistical offices should expand their mission to seize these opportunities…(More)”.
Working with AI: Real Stories of Human-Machine Collaboration
Book by Thomas H. Davenport and Steven M. Miller: “This book breaks through both the hype and the doom-and-gloom surrounding automation and the deployment of artificial intelligence-enabled—“smart”—systems at work. Management and technology experts Thomas Davenport and Steven Miller show that, contrary to widespread predictions, prescriptions, and denunciations, AI is not primarily a job destroyer. Rather, AI changes the way we work—by taking over some tasks but not entire jobs, freeing people to do other, more important and more challenging work. By offering detailed, real-world case studies of AI-augmented jobs in settings that range from finance to the factory floor, Davenport and Miller also show that AI in the workplace is not the stuff of futuristic speculation. It is happening now to many companies and workers.These cases include a digital system for life insurance underwriting that analyzes applications and third-party data in real time, allowing human underwriters to focus on more complex cases; an intelligent telemedicine platform with a chat-based interface; a machine learning-system that identifies impending train maintenance issues by analyzing diesel fuel samples; and Flippy, a robotic assistant for fast food preparation. For each one, Davenport and Miller describe in detail the work context for the system, interviewing job incumbents, managers, and technology vendors. Short “insight” chapters draw out common themes and consider the implications of human collaboration with smart systems…(More)”.
The Data Liberation Project
About: “The Data Liberation Project is a new initiative I’m launching today to identify, obtain, reformat, clean, document, publish, and disseminate government datasets of public interest. Vast troves of government data are inaccessible to the people and communities who need them most. These datasets are inaccessible. The Process:
- Identify: Through its own research, as well as through consultations with journalists, community groups, government-data experts, and others, the Data Liberation Project aims to identify a large number of datasets worth pursuing.
- Obtain: The Data Liberation Project plans to use a wide range of methods to obtain the datasets, including via Freedom of Information Act requests, intervening in lawsuits, web-scraping, and advanced document parsing. To improve public knowledge about government data systems, the Data Liberation Project also files FOIA requests for essential metadata, such as database schemas, record layouts, data dictionaries, user guides, and glossaries.
- Reformat: Many datasets are delivered to journalists and the public in difficult-to-use formats. Some may follow arcane conventions or require proprietary software to access, for instance. The Data Liberation Project will convert these datasets into open formats, and restructure them so that they can be more easily examined.
- Clean: The Data Liberation Project will not alter the raw records it receives. But when the messiness of datasets inhibits their usefulness, the project will create secondary, “clean” versions of datasets that fix these problems.
- Document: Datasets are meaningless without context, and practically useless without documentation. The Data Liberation Project will gather official documentation for each dataset into a central location. It will also fill observed gaps in the documentation through its own research, interviews, and analysis.
- Disseminate: The Data Liberation Project will not expect reporters and other members of the public simply to stumble upon these datasets. Instead, it will reach out to the newsrooms and communities that stand to benefit most from the data. The project will host hands-on workshops, webinars, and other events to help others to understand and use the data.”…(More)”