Perspective.
https://link.springer.com/chapter/10.1007/978-3-030-64246-4_2
The Data Science Revolution
Data science technology is rapidly changing the role of information technology in society and all economic sectors. Artificial Intelligence (AI) and Machine Learning (ML) are at the forefront of attention. However, data science is much broader and also includes data extraction, data preparation, data exploration, data transformation, storage and retrieval, computing infrastructures, other types of mining and learning, presentation of explanations and predictions, and the exploitation of results taking into account ethical, social, legal, and business aspects. This paper provides an overview of the field of data science also showing the main developments, thereby focusing on (1) the growing importance of learning from data (rather than modeling or programming), (2) the transfer of tasks from humans to (software) robots, and (3) the risks associated with data science (e.g., privacy problems, unfair or nontransparent decision making, and the market dominance of a few platform providers).
If AI can impersonate humans, could it fool the Patent Office?
https://link.springer.com/chapter/10.1007/978-3-030-64246-4_5
The Ethics of Artificial Intelligence
This chapter focuses on the ethics of narrow, as opposed to general AI. It makes the practical as well as the philosophical case for discussion of AI ethics. It considers ethical charters, then discusses the principal ethical issues: bias, explainability, liability for failure, harmlessness, the ethical use of data, whether AIs should have legal personality, the effects on employment and society, and AIs impersonating humans. A case study is presented of AI in personal insurance. It makes the case for regulation of AI and discusses the challenges of enacting regulation. It draws conclusions, that the benefits of AI are so valuable that the ethical risks must be managed, or the benefits may be lost because of the loss of public trust. There are grounds for optimism, notably the public consciousness of the issues, the engagement of governments and the amount of private and public investment in ethical research.
When the AI says you are guilty...
http://real.mtak.hu/117964/1/EU%20Business%20Law%20and%20Digital%20Revolution.pdf#page=51
AI Risk Assessment Tools: The Trojan Horse of the Criminal Justice System
Abstract: Risk-assessment tools are Artificial intelligence (AI) systems, which are increasingly used to ease the decision-making process for humans in criminal justice system, especially in different phases of a criminal trial: pre-arrest phase, conviction phase, parole, etc. The number of countries using this type of tools in order to ensure objectivity of the police, prosecutors or judges decision process and, in the same time to ease this process is growing. Although risk assessments tools were declared to have a positive impact on the rights of individuals accused and convicted of crimes, recent researches have shown flaws and errors in their decisions, raising concerns on the fact that they might be producing harmful effects on the rights of indicted or convicted persons. The causes of such damaging outputs of the AI systems are worth to be analysed due to their long-term impact on the criminal justice system. If the algorithms, which are fed with data provided by humans, are not “cleaned” of the discriminatory patterns, the use of such AI tools will produce more harm than benefit for the justice system. Another debate may be on the mandatory use of AI risk assessment tools by the judiciaries, because of recent research offering alarming results on their errored function or output data.
Rather negative, don’t you think?
https://brill.com/view/journals/ejcl/7/4/article-p335_335.xml
Data Regulation: A Race to…?
From the era of codification, where the law was thought to be ‘just’ a code, to today’s hybrid world where (computer) code seems to become law – at least in the eyes of those who seem to have an interesting misconception about what ‘law’ actually means or should mean – it is about two centuries time difference. The change in approach, however, took less than 20 years. It leaves the law, law makers and lawyers looking at the backlights of the technology train, waiting on a platform that together with the railway station itself is already in a state of demolition. We look at the reality around us no longer as we did before with our senses, but we look at a screen in front of us and assume that reality is only there. If what we see around us is different from what we see on the screen Hegel’s famous phrase is applied “Umso schlimmer für die Tatsachen” (too bad for the facts). In today’s language what we see on the screen are then the supposedly more correct ‘alternative facts’.
A Google ebook...
The Politics of Technology in Latin America (Volume 1): Data Protection
8 Algorithmic Law – a legal framework for Artificial Intelligence in Latin America
A Google ebook...
Research Handbook on the Sociology of Law
28 Sociology of Digital Law and Artificial Intelligence
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