AI is sending people to jail—and getting it wrong

Curated on Posted on by Stefaan Verhulst

Karen Hao atMIT Technology Review : “Using historical data to train risk assessment tools could mean that machines are copying the mistakes of the past. …

AI might not seem to have a huge personal impact if your most frequent brush with machine-learning algorithms is through Facebook’s news feed or Google’s search rankings. But at the Data for Black Lives conference last weekend, technologists, legal experts, and community activists snapped things into perspective with a discussion of America’s criminal justice system. There, an algorithm can determine the trajectory of your life. The US imprisons more people than any other country in the world. At the end of 2016, nearly 2.2 million adults were being held in prisons or jails, and an additional 4.5 million were in other correctional facilities. Put another way, 1 in 38 adult Americans was under some form of correctional supervision. The nightmarishness of this situation is one of the few issues that unite politicians on both sides of the aisle. Under immense pressure to reduce prison numbers without risking a rise in crime, courtrooms across the US have turned to automated tools in attempts to shuffle defendants through the legal system as efficiently and safely as possible. This is where the AI part of our story begins….(More)”.

Machine Learning and the Rule of Law

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Paper by Daniel L. Chen: “Predictive judicial analytics holds the promise of increasing the fairness of law. Much empirical work observes inconsistencies in judicial behavior. By predicting judicial decisions—with more or less accuracy depending on judicial attributes or case characteristics—machine learning offers an approach to detecting when judges most likely to allow extra legal biases to influence their decision making. In particular, low predictive accuracy may identify cases of judicial “indifference,” where case characteristics (interacting with judicial attributes) do no strongly dispose a judge in favor of one or another outcome. In such cases, biases may hold greater sway, implicating the fairness of the legal system….(More)”

A Survey on Sentiment Analysis

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Paper by Siva Parvathi and Yjn Lakshmi: “Sentiment analysis or Opinion mining is one of the quickest developing fields with its call for and potential advantages growing every day. With the onset of the internet and modern technology, there has been a vigorous growth in the quantity of statistics. Each character is capable of specific his/her personal ideas freely on social media. All of this facts may be analyzed and used that allows you to draw benefits and high-quality statistics.

One such idea is sentiment analysis, here, the sentiment of the problem is taken into consideration and important facts is drawn out whether it be a product evaluation or his/her opinion on whatever materialistic. A few of such packages of sentiment evaluation and the method in which they’re carried out are defined. Moreover,the possibility of every of those works to impact any destiny work is considered and explained along with the analysis as to how the previous troubles in the equal area have been overcome….(More)”.

The Age of Surveillance Capitalism

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Book by Shoshana Zuboff: “The challenges to humanity posed by the digital future, the first detailed examination of the unprecedented form of power called “surveillance capitalism,” and the quest by powerful corporations to predict and control our behavior.

Shoshana Zuboff’s interdisciplinary breadth and depth enable her to come to grips with the social, political, business, and technological meaning of the changes taking place in our time. We are at a critical juncture in the confrontation between the vast power of giant high-tech companies and government, the hidden economic logic of surveillance capitalism, and the propaganda of machine supremacy that threaten to shape and control human life. Will the brazen new methods of social engineering and behavior modification threaten individual autonomy and democratic rights and introduce extreme new forms of social inequality? Or will the promise of the digital age be one of individual empowerment and democratization?

The Age of Surveillance Capitalism is neither a hand-wringing narrative of danger and decline nor a digital fairy tale. Rather, it offers a deeply reasoned and evocative examination of the contests over the next chapter of capitalism that will decide the meaning of information civilization in the twenty-first century. The stark issue at hand is whether we will be the masters of information and machines or its slaves. …(More)”.

A Study of the Implications of Advanced Digital Technologies (Including AI Systems) for the Concept of Responsibility Within a Human Rights Framework

Curated on Posted on by Stefaan Verhulst

Report by Karen Yeung: “This study was commissioned by the Council of Europe’s Committee of experts on human rights dimensions of automated data processing and different forms of artificial intelligence (MSI-AUT). It was prompted by concerns about the potential adverse consequences of advanced digital technologies (including artificial intelligence (‘AI’)), particularly their impact on the enjoyment of human rights and fundamental freedoms. This draft report seeks to examine the implications of these technologies for the concept of responsibility, and this includes investigating where responsibility should lie for their adverse consequences. In so doing, it seeks to understand (a) how human rights and fundamental freedoms protected under the ECHR may be adversely affected by the development of AI technologies and (b) how responsibility for those risks and consequences should be allocated. 

Its methodological approach is interdisciplinary, drawing on concepts and academic scholarship from the humanities, the social sciences and, to a more limited extent, from computer science. It concludes that, if we are to take human rights seriously in a hyperconnected digital age, we cannot allow the power of our advanced digital technologies and systems, and those who develop and implement them, to be accrued and exercised without responsibility. Nations committed to protecting human rights must therefore ensure that those who wield and derive benefits from developing and deploying these technologies are held responsible for their risks and consequences. This includes obligations to ensure that there are effective and legitimate mechanisms that will operate to prevent and forestall violations to human rights which these technologies may threaten, and to attend to the health of the larger collective and shared socio-technical environment in which human rights and the rule of law are anchored….(More)”.

The Datafication of Employment

Curated on Posted on by Stefaan Verhulst

Report by Sam Adler-Bell and Michelle Miller at the Century Foundation: “We live in a surveillance society. Our every preference, inquiry, whim, desire, relationship, and fear can be seen, recorded, and monetized by thousands of prying corporate eyes. Researchers and policymakers are only just beginning to map the contours of this new economy—and reckon with its implications for equity, democracy, freedom, power, and autonomy.

For consumers, the digital age presents a devil’s bargain: in exchange for basically unfettered access to our personal data, massive corporations like Amazon, Google, and Facebook give us unprecedented connectivity, convenience, personalization, and innovation. Scholars have exposed the dangers and illusions of this bargain: the corrosion of personal liberty, the accumulation of monopoly power, the threat of digital redlining,1 predatory ad-targeting,2 and the reification of class and racial stratification.3 But less well understood is the way data—its collection, aggregation, and use—is changing the balance of power in the workplace.

This report offers some preliminary research and observations on what we call the “datafication of employment.” Our thesis is that data-mining techniques innovated in the consumer realm have moved into the workplace. Firms who’ve made a fortune selling and speculating on data acquired from consumers in the digital economy are now increasingly doing the same with data generated by workers. Not only does this corporate surveillance enable a pernicious form of rent-seeking—in which companies generate huge profits by packaging and selling worker data in marketplace hidden from workers’ eyes—but also, it opens the door to an extreme informational asymmetry in the workplace that threatens to give employers nearly total control over every aspect of employment.

The report begins with an explanation of how a regime of ubiquitous consumer surveillance came about, and how it morphed into worker surveillance and the datafication of employment. The report then offers principles for action for policymakers and advocates seeking to respond to the harmful effects of this new surveillance economy. The final sections concludes with a look forward at where the surveillance economy is going, and how researchers, labor organizers, and privacy advocates should prepare for this changing landscape….(More)”

Draft Ethics guidelines for trustworthy AI

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Working document by the European Commission’s High-Level Expert Group on Artificial Intelligence (AI HLEG): “…Artificial Intelligence (AI) is one of the most transformative forces of our time, and is bound to alter the fabric of society. It presents a great opportunity to increase prosperity and growth, which Europe must strive to achieve. Over the last decade, major advances were realised due to the availability of vast amounts of digital data, powerful computing architectures, and advances in AI techniques such as machine learning. Major AI-enabled developments in autonomous vehicles, healthcare, home/service robots, education or cybersecurity are improving the quality of our lives every day. Furthermore, AI is key for addressing many of the grand challenges facing the world, such as global health and wellbeing, climate change, reliable legal and democratic systems and others expressed in the United Nations Sustainable Development Goals.

Having the capability to generate tremendous benefits for individuals and society, AI also gives rise to certain risks that should be properly managed. Given that, on the whole, AI’s benefits outweigh its risks, we must ensure to follow the road that maximises the benefits of AI while minimising its risks. To ensure that we stay on the right track, a human-centric approach to AI is needed, forcing us to keep in mind that the development and use of AI should not be seen as a means in itself, but as having the goal to increase human well-being. Trustworthy AI will be our north star, since human beings will only be able to confidently and fully reap the benefits of AI if they can trust the technology.

Trustworthy AI has two components: (1) it should respect fundamental rights, applicable regulation and core principles and values, ensuring an “ethical purpose” and (2) it should be technically robust and reliable since, even with good intentions, a lack of technological mastery can cause unintentional harm.

These Guidelines therefore set out a framework for Trustworthy AI:

  • Chapter I deals with ensuring AI’s ethical purpose, by setting out the fundamental rights, principles and values that it should comply with.
  • From those principles, Chapter II derives guidance on the realisation of Trustworthy AI, tackling both ethical purpose and technical robustness. This is done by listing the requirements for Trustworthy AI and offering an overview of technical and non-technical methods that can be used for its implementation.
  • Chapter III subsequently operationalises the requirements by providing a concrete but nonexhaustive assessment list for Trustworthy AI. This list is then adapted to specific use cases. …(More)”

A People’s Guide to AI

Curated on Posted on by Stefaan Verhulst

Booklet by Mimi Onuoha and Diana Nucera: “..this booklet aims to fill the gaps in information about AI by creating accessible materials that inform communities and allow them to identify what their ideal futures with AI can look like. Although the contents of this booklet focus on demystifying AI, we find it important to state that the benefits of any technology should be felt by all of us. Too often, the challenges presented by new technology spell out yet another tale of racism, sexism, gender inequality, ableism, and lack of consent within digital culture.

The path to a fair future starts with the humans behind the machines, not the machines themselves. Self-reflection and a radical transformation of our relationships to our environment and each other are at the heart of combating structural inequality. But understanding what it takes to create a fair and just society is the first step. In creating this booklet, we start from the belief that equity begins with education…For those who wish to learn more about specific topics, we recommend looking at the table of contents and choosing sections to read. For more hands-on learners, we have also included a number of workbook activities that allow the material to be explored in a more active fashion.

We hope that this booklet inspires and informs those who are developing emerging technologies to reflect on how these technologies can impact our societies. We also hope that this booklet inspires and informs black, brown, indigenous, and immigrant communities to reclaim technology as a tool of liberation…(More)”.

The Everyday Life of an Algorithm

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Book by Daniel Neyland: “This open access book begins with an algorithm–a set of IF…THEN rules used in the development of a new, ethical, video surveillance architecture for transport hubs. Readers are invited to follow the algorithm over three years, charting its everyday life. Questions of ethics, transparency, accountability and market value must be grasped by the algorithm in a series of ever more demanding forms of experimentation. Here the algorithm must prove its ability to get a grip on everyday life if it is to become an ordinary feature of the settings where it is being put to work. Through investigating the everyday life of the algorithm, the book opens a conversation with existing social science research that tends to focus on the power and opacity of algorithms. In this book we have unique access to the algorithm’s design, development and testing, but can also bear witness to its fragility and dependency on others….(More)”.

Trusting Intelligent Machines: Deepening Trust Within Socio-Technical Systems

Curated on Posted on by Stefaan Verhulst

Peter Andras et al in IEEE Technology and Society Magazine: “Intelligent machines have reached capabilities that go beyond a level that a human being can fully comprehend without sufficiently detailed understanding of the underlying mechanisms. The choice of moves in the game Go (generated by Deep Mind’s Alpha Go Zero) are an impressive example of an artificial intelligence system calculating results that even a human expert for the game can hardly retrace. But this is, quite literally, a toy example. In reality, intelligent algorithms are encroaching more and more into our everyday lives, be it through algorithms that recommend products for us to buy, or whole systems such as driverless vehicles. We are delegating ever more aspects of our daily routines to machines, and this trend looks set to continue in the future. Indeed, continued economic growth is set to depend on it. The nature of human-computer interaction in the world that the digital transformation is creating will require (mutual) trust between humans and intelligent, or seemingly intelligent, machines. But what does it mean to trust an intelligent machine? How can trust be established between human societies and intelligent machines?…(More)”.