Implementing User Rights for Research in the Field of Artificial Intelligence: A Call for Action at International Level external link

Flynn, S., Geiger, C. & Quintais, J.
Kluwer Copyright Blog, 2020

Abstract

A version of this post was also published on the InfoJustice website: http://infojustice.org/archives/42260

Artificial intelligence, Auteursrecht, frontpage

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Implementing User Rights for Research in the Field of Artificial Intelligence: A Call for International Action external link

Flynn, S., Geiger, C., Quintais, J., Margoni, T., Sag, M., Guibault, L. & Carroll, M.
European Intellectual Property Review, vol. 2020, num: 7, 2020

Abstract

Last year, before the onset of a global pandemic highlighted the critical and urgent need for technology-enabled scientific research, the World Intellectual Property Organization (WIPO) launched an inquiry into issues at the intersection of intellectual property (IP) and artificial intelligence (AI). We contributed comments to that inquiry, with a focus on the application of copyright to the use of text and data mining (TDM) technology. This article describes some of the most salient points of our submission and concludes by stressing the need for international leadership on this important topic. WIPO could help fill the current gap on international leadership, including by providing guidance on the diverse mechanisms that countries may use to authorize TDM research and serving as a forum for the adoption of rules permitting cross-border TDM projects.

Artificial intelligence, Auteursrecht, frontpage, machine learning, tdm, Text and Data Mining (TDM)

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Strengthening legal protection against discrimination by algorithms and artificial intelligence external link

The International Journal of Human Rights, 2020

Abstract

Algorithmic decision-making and other types of artificial intelligence (AI) can be used to predict who will commit crime, who will be a good employee, who will default on a loan, etc. However, algorithmic decision-making can also threaten human rights, such as the right to non-discrimination. The paper evaluates current legal protection in Europe against discriminatory algorithmic decisions. The paper shows that non-discrimination law, in particular through the concept of indirect discrimination, prohibits many types of algorithmic discrimination. Data protection law could also help to defend people against discrimination. Proper enforcement of non-discrimination law and data protection law could help to protect people. However, the paper shows that both legal instruments have severe weaknesses when applied to artificial intelligence. The paper suggests how enforcement of current rules can be improved. The paper also explores whether additional rules are needed. The paper argues for sector-specific – rather than general – rules, and outlines an approach to regulate algorithmic decision-making.

algoritmes, Artificial intelligence, discriminatie, frontpage, GDPR, Privacy

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Implications of AI-driven tools in the media for freedom of expression external link

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Background Paper to the Ministerial Conference "Artificial Intelligence - Intelligent Politics: Challenges and opportunities for media and democracy, Cyprus, 28-29 May 2020."

Artificial intelligence, Freedom of expression, frontpage, Media law

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Joint Comment to WIPO on Copyright and Artificial Intelligence external link

Flynn, S., Carroll, M., Sag, M., Guibault, L., Margoni, T., Butler, B., Rocha de Souza, A., Bogataj Jancic, M., Jaszi, P., Quintais, J., Geiger, C., Ncube, C., White, B., Scaria, A.G., Botero, C. & Craig, C.
2020

Abstract

On December 13, 2019, WIPO invited member states and all other interested parties to provide comments and suggestions to help define the issues related to intellectual property (IP) and artificial intelligence (AI) based on a Draft Issues Paper on IP Policy and AI. These comments will be used to prepare a revised issues paper for discussion at the second session of the WIPO Conversation on IP and AI. This Joint Comment is made in response to WIPO’s Public Consultation on AI and IP Policy and is endorsed by 16 members of the Global Expert Network on Copyright User Rights.

Artificial intelligence, Auteursrecht, frontpage, WIPO

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Prospective Policy Study on Artificial Intelligence and EU Trade Policy external link

Irion, K. & Williams, J.
2020

Abstract

Artificial intelligence is poised to be 21st century’s most transformative general purpose technology that mankind ever availed itself of. Artificial intelligence is a catch-all for technologies that can carry out complex processes fairly independently by learning from data. In the form of popular digital services and products, applied artificial intelligence is seeping into our daily lives, for example, as personal digital assistants or as autopiloting of self-driving cars. This is just the beginning of a development over the course of which artificial intelligence will generate transformative products and services that will alter world trade patterns. Artificial intelligence holds enormous promise for our information civilization if we get the governance of artificial intelligence right. What makes artificial intelligence even more fascinating is that the technology can be deployed fairly location-independent. Cross-border trade in digital services which incorporate applied artificial intelligence into their software architecture is ever increasing. That brings artificial intelligence within the purview of international trade law, such as the General Agreement on Trade in Services (GATS) and ongoing negotiations at the World Trade Organization (WTO) on trade related aspects of electronic commerce. The Dutch Ministry of Foreign Affairs commissioned this study to generate knowledge about the interface between international trade law and European norms and values in the use of artificial intelligence.

Artificial intelligence, EU law, Human rights, Transparency, WTO law

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Can Machines be Authors? external link

Kluwer Copyright Blog, vol. 2019, 2019

Artificial intelligence, Copyright, frontpage

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The Netherlands in ‘Automating Society – Taking Stock of Automated Decision-Making in the EU’ external link

pp: 93-102, 2019

Abstract

Systems for automated decision-making or decision support (ADM) are on the rise in EU countries: Profiling job applicants based on their personal emails in Finland, allocating treatment for patients in the public health system in Italy, sorting the unemployed in Poland, automatically identifying children vulnerable to neglect in Denmark, detecting welfare fraud in the Netherlands, credit scoring systems in many EU countries – the range of applications has broadened to almost all aspects of daily life. This begs a lot of questions: Do we need new laws? Do we need new oversight institutions? Who do we fund to develop answers to the challenges ahead? Where should we invest? How do we enable citizens – patients, employees, consumers – to deal with this? For the report “Automating Society – Taking Stock of Automated Decision-Making in the EU”, our experts have looked at the situation at the EU level but also in 12 Member States: Belgium, Denmark, Finland, France, Germany, Italy, Netherlands Poland, Slovenia, Spain, Sweden and the UK. We assessed not only the political discussions and initiatives in these countries but also present a section “ADM in Action” for all states, listing examples of automated decision-making already in use. This is the first time a comprehensive study has been done on the state of automated decision-making in Europe.

algorithms, algoritmes, Artificial intelligence, EU, frontpage, kunstmatige intelligentie, NGO

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Discrimination, artificial intelligence, and algorithmic decision-making external link

vol. 2019, 2019

Abstract

This report, written for the Anti-discrimination department of the Council of Europe, concerns discrimination caused by algorithmic decision-making and other types of artificial intelligence (AI). AI advances important goals, such as efficiency, health and economic growth but it can also have discriminatory effects, for instance when AI systems learn from biased human decisions. In the public and the private sector, organisations can take AI-driven decisions with farreaching effects for people. Public sector bodies can use AI for predictive policing for example, or for making decisions on eligibility for pension payments, housing assistance or unemployment benefits. In the private sector, AI can be used to select job applicants, and banks can use AI to decide whether to grant individual consumers credit and set interest rates for them. Moreover, many small decisions, taken together, can have large effects. By way of illustration, AI-driven price discrimination could lead to certain groups in society consistently paying more. The most relevant legal tools to mitigate the risks of AI-driven discrimination are nondiscrimination law and data protection law. If effectively enforced, both these legal tools could help to fight illegal discrimination. Council of Europe member States, human rights monitoring bodies, such as the European Commission against Racism and Intolerance, and Equality Bodies should aim for better enforcement of current nondiscrimination norms. But AI also opens the way for new types of unfair differentiation (some might say discrimination) that escape current laws. Most non-discrimination statutes apply only to discrimination on the basis of protected characteristics, such as skin colour. Such statutes do not apply if an AI system invents new classes, which do not correlate with protected characteristics, to differentiate between people. Such differentiation could still be unfair, however, for instance when it reinforces social inequality. We probably need additional regulation to protect fairness and human rights in the area of AI. But regulating AI in general is not the right approach, as the use of AI systems is too varied for one set of rules. In different sectors, different values are at stake, and different problems arise. Therefore, sector-specific rules should be considered. More research and debate are needed.

Artificial intelligence, discriminatie, frontpage, kunstmatige intelligentie, Mensenrechten

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Democratizing algorithmic news recommenders: how to materialize voice in a technologically saturated media ecosystem external link

Philosophical Transactions of the Royal Society A, vol. 376, num: 2135, pp: 1-21, 2018

Abstract

The deployment of various forms of AI, most notably of machine learning algorithms, radically transforms many domains of social life. In this paper we focus on the news industry, where different algorithms are used to customize news offerings to increasingly specific audience preferences. While this personalization of news enables media organizations to be more receptive to their audience, it can be questioned whether current deployments of algorithmic news recommenders (ANR) live up to their emancipatory promise. Like in various other domains, people have little knowledge of what personal data is used and how such algorithmic curation comes about, let alone that they have any concrete ways to influence these data-driven processes. Instead of going down the intricate avenue of trying to make ANR more transparent, we explore in this article ways to give people more influence over the information news recommendation algorithms provide by thinking about and enabling possibilities to express voice. After differentiating four ideal typical modalities of expressing voice (alternation, awareness, adjustment and obfuscation) which are illustrated with currently existing empirical examples, we present and argue for algorithmic recommender personae as a way for people to take more control over the algorithms that curate people's news provision.

access to information, algoritmes, Artificial intelligence, frontpage, news, persona, Personalisation, right to receive information, user agency

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