Sunday, July 05, 2020


Someone watches...
The State of AI Ethics Report (June 2020)
With this inaugural edition of the State of AI Ethics we hope to bring forward the most important developments that caught our attention at the Montreal AI Ethics Institute this past quarter. Our goal is to help you navigate this ever-evolving field swiftly and allow you and your organization to make informed decisions. This pulse-check for the state of discourse, research, and development is geared towards researchers and practitioners alike who are making decisions on behalf of their organizations in considering the societal impacts of AI-enabled solutions. We cover a wide set of areas in this report spanning Agency and Responsibility, Security and Risk, Disinformation, Jobs and Labor, the Future of AI Ethics, and more. Our staff has worked tirelessly over the past quarter surfacing signal from the noise so that you are equipped with the right tools and knowledge to confidently tread this complex yet consequential domain.




As we made the CFO responsible for the accuracy of financial reporting?
Could regulating the creators deliver trustworthy AI?
Is a new regulated profession, such as Artificial Intelligence (AI) Architect who is responsible and accountable for AI outputs necessary to ensure trustworthy AI? AI is becoming all pervasive and is often deployed in everyday technologies, devices and services without our knowledge. There is heightened awareness of AI in recent years which has brought with it fear. This fear is compounded by the inability to point to a trustworthy source of AI, however even the term "trustworthy AI" itself is troublesome. Some consider trustworthy AI to be that which complies with relevant laws, while others point to the requirement to comply with ethics and standards (whether in addition to or in isolation of the law). This immediately raises questions of whose ethics and which standards should be applied and whether these are sufficient to produce trustworthy AI in any event.




When you think, ‘That’s not right?’
Contestable Black Boxes
The right to contest a decision with consequences on individuals or the society is a well-established democratic right. Despite this right also being explicitly included in GDPR in reference to automated decision-making, its study seems to have received much less attention in the AI literature compared, for example, to the right for explanation. This paper investigates the type of assurances that are needed in the contesting process when algorithmic black-boxes are involved, opening new questions about the interplay of contestability and explainability. We argue that specialised complementary methodologies to evaluate automated decision-making in the case of a particular decision being contested need to be developed. Further, we propose a combination of well-established software engineering and rule-based approaches as a possible socio-technical solution to the issue of contestability, one of the new democratic challenges posed by the automation of decision making.




Further definitions required.
ISSUES OF CONSTRUCTION OF LEGAL DEFINITIONS IN THE FIELD OF ARTIFICIAL INTELLIGENCE
The study of the problems of the formation of the conceptual apparatus in the field of legal support of artificial intelligence to develop effective legal solutions in order to regulate new digital technologies. The work is based on a combination of general scientific and special legal methods, including analysis, description, generalization, comparative law. The formation of legal definitions of artificial intelligence and related concepts (robot, cyberphysical system, etc.) requires the identification of the main legal features of artificial intelligence. The following key characteristics of artificial intelligence are identified: optional hardware implementation; the ability of the system to analyze the environment; autonomy in operation; the ability to accumulate experience, its assessment and implementation of the task of self-learning; the presence of "intelligence", described through the categories of "rationality", "rationality" or simply the ability to "think like a person" or "act like a person" in all or in narrowly defined circumstances.




A clear downside?
Artificial Intelligence and Copyright Law in a European context - A study on the protection of works produced by AI-systems
This master thesis discusses current copyright rules and if there is presently a copyright protection for these types of works. There is a possibility to protect works that have been generated by AI’s. However, this is only possible if a human is using the AI as a “tool”, in order to reach a certain end-goal. There has to be a clear link between the human author and the machine, otherwise neither authorship nor originality can be established. Ultimately, in a scenario where such a link is missing, the work would fall into public domain.
The beforementioned is followed by possible solutions for protecting these works in the future. In fact, it is interesting to look into the legislation of countries such as the UK, the US and EU Member States in order to study their ways of protecting similar types of works. These solutions will treat topics such as AI as an “employee”, the UK concept of computer generated works and the attribution of legal personhood to AI-systems. Additionally, there might be a need for changing the structure of the current EU copyright rules, namely by lowering the thresholds for protection, in order to widen the possibilities to give copyright protection to AI-generated works.
Ultimately, the thesis finds that the best way of protecting AI-generated works would be, to develop a new sui generis rule for AI-generated works. This solution is the most likely to see the day, as it is a flexible and easy way of attributing copyright protection without changing and lowering the traditional copyright thresholds for protection.



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