Our weekly news roundup for Jan 15 - Jan 21: Including AI in Finance, political campaigns, social profiling, the workplace, the problem of identifying health data, and some pieces on explainability and governance.
Everything We Do Tells Something About Our Health - Including Our Taste in Music
Much of our data exhaust is rich enough that it can be used to generate accurate inferences about us in domains unrelated to context of collection. Machine learning analysis of large sets of data about our music listening habits can reveal information about our physical and mental health. This information, if directly present, would be subject to regulatory and ethical norms.
"A crucial question is: what exactly is health data? Does it comprise the data from medical treatment and investigation, or is it more than that? In his research, Hooghiemstra refers to medical investigations, also mentioning wearables and apps. But where, precisely, is the line between what is and what is not health data?"
AI – Enabled Innovation, Part 1: Regulatory Intervention & AI in Financial Services
The first of a two-part series on AI in Finance:
"Financial services regulators are promoting principles and giving guidance through public statements to set the expectation that firms need to ensure their governance model is fit for purpose when applied to AI enabled innovation. In time, these regulators will become more proactive in asking firms to demonstrate they fully understand their data assets and to explain how that data is exploited and how the associated risk is mitigated when using AI – enabled technologies. Financial services firms should develop a coherent AI strategy now in a way that anticipates how they will answer that question when it inevitably comes."
Towards ethical and socio-legal governance in AI
"Many high-level ethics guidelines for AI have been produced in the past few years. It is time to work towards concrete policies within the context of existing moral, legal and cultural values, say Andreas Theodorou and Virginia Dignum."
Artificial intelligence: DeepMind unlocks secrets of human brain using AI learning technique
Researchers at Google-owned DeepMind discovered that a recent development in computer science regarding reinforcement learning could be applied to how the brain’s dopamine system works.
Digital Political Ethics: Aligning Principles with Practice
"This report is the fruit of a bipartisan report to identify areas of agreement among key stakeholders concerning ethical principles and best practices in the conduct of digital campaigning in the United States. Although many have raised concerns about the potential for digital technologies to weaken or undermine democracy, the voices of digital political practitioners are largely absent from this discussion."
Algorithms at Work: The New Contested Terrain of Control
"We find that algorithmic control in theworkplace operates through six main mechanisms, which we call the“6Rs”—employers can use algorithms to direct workers by restrictingand recommending, evaluate workers by recording and rating, and discipline workers by replacing and rewarding. We also discuss several key insights regarding algorithmic control."
Black-Boxed Politics:Opacity is a Choice in AI Systems
"There are many myths and misconceptions about AI, but in cases where these systems are being used in sensitive, high-risk scenarios such as public health and criminal justice, arguably the most damaging msconception is that these systems are ‘black boxes’ about which we simply cannot know anything."
The US just released 10 principles that it hopes will make AI safer
"The White House has released 10 principles for government agencies to adhere to when proposing new AI regulations for the private sector."
Booker beware: Airbnb can scan your online life to see if you’re a suitable guest
"Details have emerged of its “trait analyser” software built to scour the web to assess users’ “trustworthiness and compatibility” as well as their “behavioural and personality traits” in a bid to forecast suitability to rent a property. "
Beyond Bias: Contextualizing “Ethical AI” Within the History of Exploitation and Innovation in Medical Research
This is from late December, but it just reached us and is worth a read: "It’s time for us to move beyond “bias” as the anchor point for our efforts to build ethical and fair algorithms."