Violating privacy by algorithm?
DWP urged to reveal algorithm that ‘targets’ disabled for benefit fraud
Disabled people are being subjected to stressful checks and months of frustrating bureaucracy after being identified as potential benefit fraudsters by an algorithm the government is refusing to disclose, according to a new legal challenge.
A group in Manchester has launched the action after mounting testimony from disabled people in the area that they were being disproportionately targeted for benefit fraud investigations. Some said they were living in “fear of the brown envelope” showing their case was being investigated. Others said they had received a phone call, without explanation as to why they had been flagged.
The Department for Work and Pensions (DWP) has previously conceded that it uses “cutting-edge artificial intelligence” to track possible fraud but has so far rebuffed attempts to explain how the algorithm behind the system was compiled. Campaigners say that once flagged, those being examined can face an invasive and humiliating investigation lasting up to a year.
Fertile ground for recruiting Privacy Lawyers?
https://www.theregister.com/2021/11/20/in_brief_ai/
AI surveillance software increasingly used to make sure contract lawyers are doing their jobs at home
Contract lawyers are increasingly working under the thumb of facial-recognition software as they continue to work from home during the COVID-19 pandemic.
The technology is hit-and-miss, judging from interviews with more than two dozen American attorneys conducted by the Washington Post. To make sure these contract lawyers, who take on short term-gigs, are working as expected and are handling sensitive information appropriately, their every move is followed by webcams.
The monitoring software is mandated by their employers, and is used to control access to the legal documents that need to be reviewed. If the system thinks someone else is looking at the files on the computer, or equipment has been set up to record information from the screen, the user is booted out.
(Related)
How wearable tech can reveal your performance at work
Not just keeping you fit and healthy, data from fitness trackers and smart watches can also predict individual job performances as workers travel to and from the office wearing those devices, says a study.
Previous research on commuting indicates that stress, anxiety, and frustration from commuting can lead to a less efficient workforce and an increased counterproductive work behaviour.
Researchers from Dartmouth College in the US built mobile sensing machine learning (ML) models to accurately predict job performance via data derived from wearable devices.
… "Compared to low performers, high performers display greater consistency in the time they arrive and leave work," said Pino Audia, a co-author of the study.
"This dramatically reduces the negative impacts of commuting variability and suggests that the secret to high performance may lie in sticking to better routines." While high performers had physiological indicators that are consistent with physical fitness and stress resilience, low performers had higher stress levels in the times before, during, and after commutes.
When laws conflict?
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3961863
Legal Opacity: Artificial Intelligence’s Sticky Wicket
Proponents of artificial intelligence (“AI”) transparency have carefully illustrated the many ways in which transparency may be beneficial to prevent safety and unfairness issues, to promote innovation, and to effectively provide recovery or support due process in lawsuits. However, impediments to transparency goals, described as opacity, or the “black-box” nature of AI, present significant issues for promoting these goals.
An undertheorized perspective on opacity is legal opacity, where competitive, and often discretionary legal choices, coupled with regulatory barriers create opacity. Although legal opacity does not specifically affect AI only, the combination of technical opacity in AI systems with legal opacity amounts to a nearly insurmountable barrier to transparency goals. Types of legal opacity, including trade secrecy status, contractual provisions that promote confidentiality and data ownership restrictions, and privacy law independently and cumulatively make the black box substantially opaquer.
The degree to which legal opacity should be limited or disincentivized depends on the specific sector and transparency goals of specific AI technologies, technologies which may dramatically affect people’s lives or may simply be introduced for convenience. This Response proposes a contextual approach to transparency: Legal opacity may be limited in situations where the individual or patient benefits, when data sharing and technology disclosure can be incentivized, or in a protected state when transparency and explanation are necessary.
Everything you ever wanted to know?
https://www.emerald.com/insight/content/doi/10.1108/S2398-601820210000008007/full/html
The Big Data World: Benefits, Threats and Ethical Challenges
Advances in Big Data, artificial Intelligence and data-driven innovation bring enormous benefits for the overall society and for different sectors. By contrast, their misuse can lead to data workflows bypassing the intent of privacy and data protection law, as well as of ethical mandates. It may be referred to as the ‘creep factor’ of Big Data, and needs to be tackled right away, especially considering that we are moving towards the ‘datafication’ of society, where devices to capture, collect, store and process data are becoming ever-cheaper and faster, whilst the computational power is continuously increasing. If using Big Data in truly anonymisable ways, within an ethically sound and societally focussed framework, is capable of acting as an enabler of sustainable development, using Big Data outside such a framework poses a number of threats, potential hurdles and multiple ethical challenges. Some examples are the impact on privacy caused by new surveillance tools and data gathering techniques, including also group privacy, high-tech profiling, automated decision making and discriminatory practices. In our society, everything can be given a score and critical life changing opportunities are increasingly determined by such scoring systems, often obtained through secret predictive algorithms applied to data to determine who has value. It is therefore essential to guarantee the fairness and accurateness of such scoring systems and that the decisions relying upon them are realised in a legal and ethical manner, avoiding the risk of stigmatisation capable of affecting individuals’ opportunities. Likewise, it is necessary to prevent the so-called ‘social cooling’. This represents the long-term negative side effects of the data-driven innovation, in particular of such scoring systems and of the reputation economy. It is reflected in terms, for instance, of self-censorship, risk-aversion and lack of exercise of free speech generated by increasingly intrusive Big Data practices lacking an ethical foundation. Another key ethics dimension pertains to human-data interaction in Internet of Things (IoT) environments, which is increasing the volume of data collected, the speed of the process and the variety of data sources. It is urgent to further investigate aspects like the ‘ownership’ of data and other hurdles, especially considering that the regulatory landscape is developing at a much slower pace than IoT and the evolution of Big Data technologies. These are only some examples of the issues and consequences that Big Data raise, which require adequate measures in response to the ‘data trust deficit’, moving not towards the prohibition of the collection of data but rather towards the identification and prohibition of their misuse and unfair behaviours and treatments, once government and companies have such data. At the same time, the debate should further investigate ‘data altruism’, deepening how the increasing amounts of data in our society can be concretely used for public good and the best implementation modalities.
Perhaps an AI detective agency?
https://journals.sagepub.com/doi/abs/10.1177/20322844211057019
Legal challenges in bringing AI evidence to the criminal courtroom
Artificial Intelligence (AI) is rapidly transforming the criminal justice system. One of the promising applications of AI in this field is the gathering and processing of evidence to investigate and prosecute crime. Despite its great potential, AI evidence also generates novel challenges to the requirements in the European criminal law landscape. This study aims to contribute to the burgeoning body of work on AI in criminal justice, elaborating upon an issue that has not received sufficient attention: the challenges triggered by AI evidence in criminal proceedings. The analysis is based on the norms and standards for evidence and fair trial, which are fleshed out in a large amount of European case law. Through the lens of AI evidence, this contribution aims to reflect on these issues and offer new perspectives, providing recommendations that would help address the identified concerns and ensure that the fair trial standards are effectively respected in the criminal courtroom.
Next article should discuss how to find a jury of AI peers.
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3963422
The Legal Quandary When AI Is The Criminal
One assumption about AI is that there will always be a human held accountable for any bad acts that the AI perchance commits. Some though question this assumption and emphasize that the AI might presumably “act on its own” or that it will veer far from its programming or that the programmers that created the AI will be impossible to identify. [Or the programmers were themselves AI? Bob] A legal quandary is ostensibly raised via the advent of such AI that goes criminally bad (or was bad, to begin with).
Making new law…
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3963426
Core Principles of Justice And Respective AI Impacts
A vital question worth asking is what will happen to our venerated principles of justice due to the advent of AI in the law. To grapple with that crucial matter, we first clarify the precepts of justice to be considered and then stepwise analyze how AI will impact each of them.
(Related)
https://scholar.law.colorado.edu/cgi/viewcontent.cgi?article=2500&context=articles
The Law of AI
The question of whether new technology requires new law is central to the field of law and technology. From Frank Easterbrook’s “law of the horse” to Ryan Calo’s law of robotics, scholars have debated the what, why, and how of technological, social, and legal co-development and construction. Given how rarely lawmakers create new legal regimes around a particular technology, the EU’s proposed “AI Act” (Regulation of the European Parliament and of the Council Laying Down Harmonised Rules on Artificial Intelligence and Amending Certain Union Legislative Acts) should put tech-law scholars on high alert. Leaked early this spring and officially released in April 2021, the AI Act aims to establish a comprehensive European approach to AI risk-management and compliance, including bans on some AI systems.
In Demystifying the Draft EU Artificial Intelligence Act, Michael Veale and Frederik Zuiderveen Borgesius provide a helpful and evenhanded entrée into this “world-first attempt at horizontal regulation of AI systems.” One the one hand, they admire the Act’s “sensible” aspects, including its risk-based approach, prohibitions of certain systems, and attempts at establishing public transparency. On the other, they note its “severe weaknesses” including its reliance on “1980s product safety regulation” and “standardisation bodies with no fundamental rights experience.” For U.S. (and EU!) readers looking for a thoughtful overview and contextualization of a complex and somewhat inscrutable new legal system, this Article brings much to the table at a relatively concise length
Obvious?
https://orbilu.uni.lu/bitstream/10993/48564/1/Blount%20RIDP%20PDF.pdf
APPLYING THE PRESUMPTION OF INNOCENCE TO POLICING WITH AI
This paper argues that predictive policing, which relies upon former arrest records, hinders the future application of the presumption of innocence. This is established by positing that predictive policing is comparable to traditional criminal investigations in substance and scope. Police records generally do not clarify whether former charges result in dismissal or acquittal, or conversely, conviction. Therefore, police as state actors may unlawfully act in reliance on an individual’s former arrest record, despite a favourable disposition. Accordingly, it is argued that the presumption of innocence as a fair trial right may be effectively nullified by predictive policing.
(Related) The next step…
https://orbi.uliege.be/handle/2268/264969
The Use of AI Tools in Criminal Courts: Justice Done and Seen To Be Done?
Artificial intelligence (hereafter: AI) is impacting all sectors of society these days, including the criminal justice area. AI has indeed become an important tool in this area, whether for citizens seeking justice, legal practitioners or police and judicial authorities. While there is already a large body of literature on the prediction and detection of crime, this article focuses on the current and future role of AI in the adjudication of criminal cases. A distinction will be made between AI systems that facilitate adjudication and those that could, in part or wholly, replace human judges. At each step, we will give some concrete examples and evaluate what are, or could be, the advantages and disadvantages of such systems when used in criminal courts.
AI is never cruel…
REVIEWING ALGORITHMIC DECISION MAKING IN ADMINISTRATIVE LAW
Artificial intelligence is perhaps the most significant technological shift since the popularization of the Internet in the waning years of the 20th century. Artificial intelligence promises to affect most parts of the modern economy, from trucking and transportation to medical care and research. Our legal system has already begun to contemplate how artificially intelligent decision making systems are likely to affect procedural fairness and access to justice. These effects have been underexamined in the area of administrative law, in which artificially intelligent systems might be used to expedite decision making, ensure the relatively equal treatment of like cases, and ward against discrimination. But the adoption of
artificially intelligent systems by administrative decision makers also raises serious questions. This essay focuses on one such question: whether the administrative decisions taken by artificially intelligent systems are capable of meeting the duty of procedural fairness owed to the subjects of such decisions. This essay is arranged in three sections. In the first, I briefly outline the increasing use of artificially intelligent systems in the administrative context. I focus primarily on machine learning algorithms and will describe the technical challenge of inexplicability that they raise. In the second section, I set out the duty of administrative decision makers to explain their reasoning in certain contexts. In the third section, I argue that administrative processes that use artificially intelligent systems will likely complicate the effective discharge of this duty. Individuals subject to certain kinds of administrative decisions may be deprived of the reasons to which they are entitled. I argue that artificial intelligence might prompt us to rethink reason giving practices in administrative law.
Ethical medicine. Take two tablets and call me in the morning?
https://ieeexplore.ieee.org/abstract/document/9597180
Regulatory Framework of Artificial Intelligence in Healthcare
This paper provides an overview of the application of artificial intelligence in healthcare and what it means in many ways. These aspects will be the privacy that this new technology offers us versus the availability of information that this technology needs. We will also discuss the regulatory framework in the most important areas of the world such as the United States and Europe, comparing the laws and strategies that organizations have used to preserve the security and control of artificial intelligence in healthcare. As a consequence, we will expose the ethical challenges posed by the entry of this new technology into our lives. We will also place ourselves in the current framework of the situation of artificial intelligence today, how it emerged, and its history over the years. To summarize, some conclusions have been proposed to conclude, and a personal opinion of the authors is about everything discussed throughout the paperwork.
Backing into ethics?
https://ieeexplore.ieee.org/abstract/document/9611065
8 The Ethics of Artificial Intelligence
Chapter Abstract: The dramatic theoretical and practical progress of artificial intelligence in the past decade has raised serious concerns about its ethical consequences. In response, more than eighty organizations have proposed sets of principles for ethical artificial intelligence. The proposed principles overlap in their concern with values such as transparency, justice, fairness, human benefits, avoiding harm, responsibility, and privacy. But no substantive discussion of how principles for ethical AI can be analyzed, justified, and reconciled has taken place. Moreover, the values assumed by these principles have received little analysis and assessment. Perhaps issues about principles and values can be evaded by Stuart Russell's proposal that beneficial AI concerns people's preferences rather than their ethical principles and values.
Tools & Techniques
https://www.makeuseof.com/tag/best-walkie-talkie-app/
The Best Two-Way Walkie Talkie Apps for Android and iPhone
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