The next generation of data ethics tools – The ODI

Digital Ethics
Does Your AI Model Know What It’s Talking About? Here’s One Way To Find Out.
When you ask AI models a question, they are programmed to give you an answer—even if they know little to nothing about the subject. Model overconfidence is the reason why many AI deployments fail. But a solution exists—and if your model isn't using it, you might not want to trust its judgments.
WSJ News Exclusive | App Taps Unwitting Users Abroad to Gather Open-Source Intelligence
The Premise app pays users, many in the developing world, to do tasks like taking photos and completing surveys for clients including the U.S. military.
Carl T. Bergstrom on Twitter
1. We have a new paper out in PNAS today, in which we address the harm wrought by dramatically restructuring human communication of the span of a decade, with no aim other than selling ads. It might be the most important paper of my career.https://t.co/sBWZtr9ZyE— Carl T. Bergstrom (@CT_Bergstrom) June 21, 2021
Stewardship of global collective behavior
Collective behavior provides a framework for understanding how the actions and properties of groups emerge from the way individuals generate and share information. In humans, information flows were initially shaped by natural selection yet are increasingly structured by emerging communication technologies. Our larger, more complex social networks now transfer high-fidelity information over vast distances at low cost. The digital age and the rise of social media have accelerated changes to our social systems, with poorly understood functional consequences. This gap in our knowledge represents a principal challenge to scientific progress, democracy, and actions to address global crises. We argue that the study of collective behavior must rise to a “crisis discipline” just as medicine, conservation, and climate science have, with a focus on providing actionable insight to policymakers and regulators for the stewardship of social systems.
There are no data underlying this work.
Ethical Concerns in the future of AI
Artificial intelligence (AI) is rapidly improving, becoming an embedded feature of almost any type of software platform you can imagine, and serving as the foundation for countless types of digital assistants. It’s used in everything from data analytics and pattern recognition to automation and speech replication.
The potential of this technology has sparked imaginative minds for decade...
Confiding in Con Men: U.S. Privacy Law, the GDPR, and Information Fiduciaries by Lindsey Barrett :: SSRN
In scope, ambition, and animating philosophy, American privacy law and Europe’s General Data Protection Regulation are almost diametric opposites. The GDPR’s am
Carpenter's Consumers by Lindsey Barrett :: SSRN
The laws governing what data corporations can collect heavily influence the extent to which law enforcement can pry into our lives. Consumer privacy laws have f
Model(ing) Privacy: Empirical Approaches to Privacy Law & Governance by Lindsey Barrett :: SSRN
Privacy can be difficult for people to conceptualize, including for the policymakers charged with designing, interpreting, and enforcing privacy law. In both co
Accidental Wiretaps: The Implications of False Positives By Always-Listening Devices For Privacy Law & Policy by Lindsey Barrett, Ilaria Liccardi :: SSRN
Always-listening devices like smart speakers, smartphones, and other voice-activated technologies create enough privacy problems when working correctly. But the
Rejecting Test Surveillance in Higher Education by Lindsey Barrett :: SSRN
The rise of remote proctoring software during the COVID-19 pandemic illustrates the dangers of surveillance-enabled pedagogy built on the belief that students c
The Impossibility of Automating Ambiguity | Artificial Life | MIT Press
Differences Attract: An Experimental Study of Focusing in Economic Choice* | The Economic Journal | Oxford Academic
Abstract. Several behavioural models of choice assume that decision makers place more weight on attributes where options differ more, an assumption we test in a
What If Doctors Are Always Watching, but Never There?
Remote technology could save lives by monitoring health from home or outside the hospital. It could also push patients and health care providers further apart.
The essential guide to the algorithms that run your life | New Scientist
From shaping what we read and buy to diagnosing illness, algorithms play a key role in every aspect of our lives. Here’s what you need to know about the most important ones
Bias isn't the only problem with credit scores—and no, AI can't help
The biggest-ever study of real people’s mortgage data shows that predictive tools used to approve or reject loans are less accurate for minorities.
Texas thermostats adjusted remotely during heat wave residents claim
Some residents in Texas are feeling the heat despite setting their home thermostats at a comfortable temperature.
EXCLUSIVE Google searches for new measure of skin tones to curb bias in products
Alphabet Inc's (GOOGL.O) Google told Reuters this week it is developing an alternative to the industry standard method for classifying skin tones, which a growing chorus of technology researchers and dermatologists says is inadequate for assessing whether products are biased against people of color.
Mobile health and privacy: cross sectional study
Objectives To investigate whether and what user data are collected by health related mobile applications (mHealth apps), to characterise the privacy conduct of all the available mHealth apps on Google Play, and to gauge the associated risks to privacy.
Design Cross sectional study
Setting Health related apps developed for the Android mobile platform, available in the Google Play store in Australia and belonging to the medical and health and fitness categories.
Participants Users of 20 991 mHealth apps (8074 medical and 12 917 health and fitness found in the Google Play store: in-depth analysis was done on 15 838 apps that did not require a download or subscription fee compared with 8468 baseline non-mHealth apps.
Main outcome measures Primary outcomes were characterisation of the data collection operations in the apps code and of the data transmissions in the apps traffic; analysis of the primary recipients for each type of user data; presence of adverts and trackers in the app traffic; audit of the app privacy policy and compliance of the privacy conduct with the policy; and analysis of complaints in negative app reviews.
Results 88.0% (n=18 472) of mHealth apps included code that could potentially collect user data. 3.9% (n=616) of apps transmitted user information in their traffic. Most data collection operations in apps code and data transmissions in apps traffic involved external service providers (third parties). The top 50 third parties were responsible for most of the data collection operations in app code and data transmissions in app traffic (68.0% (2140), collectively). 23.0% (724) of user data transmissions occurred on insecure communication protocols. 28.1% (5903) of apps provided no privacy policies, whereas 47.0% (1479) of user data transmissions complied with the privacy policy. 1.3% (3609) of user reviews raised concerns about privacy.
Conclusions This analysis found serious problems with privacy and inconsistent privacy practices in mHealth apps. Clinicians should be aware of these and articulate them to patients when determining the benefits and risks of mHealth apps.
U.K. Privacy Chief Sounds Alarm Over Live Facial Recognition
Britain’s privacy chief issued a warning over the risks from facial recognition technology, saying people should be free to go shopping or walk around a town “without having our biometric data collected and analyzed with every step we take.”
21 States Are Now Vetting Unemployment Claims With a ‘Risky’ Facial Recognition System
ID.me has rejected some legitimate claimants in addition to fraudsters
Opinion | Google’s Privacy Backpedal Shows Why It’s So Hard Not to Be Evil
Why Google thought twice about restoring your privacy.
Experts Doubt Ethical AI Design Will Be Broadly Adopted as the Norm Within the Next Decade | Pew Research Center
A majority worries that the evolution of artificial intelligence by 2030 will continue to be primarily focused on optimizing profits and social control. Still, a portion celebrate coming AI breakthroughs that will improve life.
LAPD officers got free swag from Ring, some promoted its cameras to the public
Ring provided at least 100 LAPD officers with free devices or discounts and encouraged them to endorse and recommend its doorbell and security cameras to police and members of the public.
The Computer Girls
Checkpoints for vaccine passports
Requirements that governments and developers will need to deliver in order for any vaccine passport system to deliver societal benefit
Reema Patel on Twitter
Powerful piece from @sobia_r for @AdaLovelaceInst on minding the missing data gap when it comes to genomics data.'The underrepresentation of diverse populations in genomic datasets and studies exacerbates health inequalities.' @HealthFdn #DataDividehttps://t.co/e8QRBVDAfh— Reema Patel (@Reema__Patel) June 17, 2021
Digital ad industry accused of huge data breach
Legal action filed over volume of data shared by digital advertising firms during ad space sales.
China’s tech workers pushed to their limits by surveillance software | Financial Times
Vicious cycle of monitoring and overwork is fuelling productivity — and a backlash
Apple reportedly trialed plans for a primary care service on its own employees - The Verge
The project hasn’t moved out of a preliminary stage.