IGF 2019 WS #365 Algorithmic decision-making for the benefit of all

Organizer 1: Spielkamp Matthias, AlgorithmWatch
Organizer 2: Sriganesh Lokanathan, LIRNEasia
Organizer 3: Marc Thümmler, AlgorithmWatch
Organizer 4: Kristina Penner, AlgorithmWatch

Speaker 1: Sriganesh Lokanathan, Civil Society, Asia-Pacific Group
Speaker 2: Dearbhail Usher, Intergovernmental Organization, Asia-Pacific Group
Speaker 3: Raquel Gatto, Technical Community, Latin American and Caribbean Group (GRULAC)
Speaker 4: Solana Larsen, Private Sector, Western European and Others Group (WEOG)
Speaker 5: Olga Cavalli, Government, Latin American and Caribbean Group (GRULAC)

Policy Question(s): 

- What evidence base do we need to develop governance of AI and ADM (algorithmic decision-making) systems?
- What is the value of ethical guidelines vis-a-vis other mechanisms (standards and norms, codes of conduct, laws)?
- What oversight mechanisms do we need to develop?
- What are the relevant differences between the Global North and South in the use and governance AI and ADM?
- Is there a realistic approach to governing such systems on the global scale?

Relevance to Theme: With the evidence we present we address almost all questions that follow from the stated purpose of the Data Governance track in a fact-based manner: What approaches exist in practice, what systems are used in the real world, what questions have already arisen from their use, what answers have been developed, how have the public and different stakeholder groups reacted to this?

Relevance to Internet Governance: The Internet is the fundamental basis for the global use of AI and ADM systems, as laid out in the description of the Data Governance theme.

Format: 

Round Table - U-shape - 90 Min

Description: The use of AI in decision-making is all around us; whether we visibly see their uses or not, we are affected by them, and their impact on our lives is only set to grow. Treatment for patients in the public health system in Italy is allocated with the help of an automated system, the Danish state tries to identify children vulnerable to neglect using an algorithm, the SyRI system in the Netherlands is supposed to detect welfare fraud with the help of so-called AI, the Swedish municipality of Trelleborg has automated parts of its decision-making for the disbursement of social benefits, and the EU tests an automated lie detector at its borders in Greece, Hungary and Latvia.
At the same time, decisions concerning marginalized groups in the Global South are often based on non-representative data (irrespective of whether these are with the aid of AI or not). Countries in Africa are on their way towards a centralized, unified and biometric repository of their population, bringing with it opportunities for financial inclusion – as a result of systems to assess creditworthiness – but at the same time these raise the risk of Chinese-style citizen scoring.
Much of the debate in the field of Automated / Algorithmic Decision-Making (ADM) systems and so called Artificial Intelligence privileges discourses of lofty ethical norms. Too little is known about where and how these systems are used in practice, especially in the Global South. Too little is also discussed of the limits of technical solutions to bias predicated on a desire to optimize multiple (often conflicting) notions of fairness. The discourses also often disregard the opportunities for ADM to bring to light biases in human decisions making that hereto were difficult to reveal.
Within these disparate use-cases, it is very important to ask what constitutes context-specific, fit-for-purpose policies with regards to ADMs. To do this we need evidence that will both inform and shape the needed actions, so that ADMs could be used increase welfare and liberties, whilst also limiting their abuses through harmful surveillance, discrimination, and control.
We will share state-of-the art research about the limits of technical notions of fairness and discrimination, as well as the practice of algorithmic decision-making processes already in use: from our reports "Automating Society – Taking Stock of Automated Decision-Making in the EU", “Identity-management and citizen scoring in Africa”, the “Atlas of Automation”, the “Internet Health Report” and "Bias and the Global South: Care now? Care later? Or not at all?”.
In a first part, we will briefly present excerpts of our evidence-based research on issues of ADM from both the Global North as well as the Global South and lay out our recommendations for policies and government arrangements. In the second part we will discuss these with the participants (including government, the private sector, and the technical community) and the audience.

Expected Outcomes: - Better (shared) knowledge among stakeholders about the use of ADM/AI systems in practice
- Better (shared) knowledge among stakeholders about possible governance mechanisms for these systems
- Tangible ideas to further evolve the governance of ADM systems

Onsite Moderator: 

Spielkamp Matthias, Civil Society, Western European and Others Group (WEOG)

Online Moderator: 

Marc Thümmler, Civil Society, Western European and Others Group (WEOG)

Rapporteur: 

Kristina Penner, Civil Society, Western European and Others Group (WEOG)

Discussion Facilitation: 

Matthias is a journalist and trained facilitator with 15 years of experience facilitating conference sessions and TV discussions; he sees his role not only in keeping time but preparing concrete questions for the speakers and audience, including the online participants.

Online Participation: 

We will announce the possibility to participate via our session outreach (including Twitter, see c) below). The online moderator will then collect questions and comments and feed them into the roundtable discussion.

Proposed Additional Tools: Via twitter. We have several accounts with a combined number of more than 100K followers (@internetsociety, @unglobalpulse, @algorithmwatch, @spielkamp), so with a hashtag dedicated to the session we'll be a able to solicit a lot of participation from around the world.

SDGs: 

GOAL 3: Good Health and Well-Being
GOAL 5: Gender Equality
GOAL 8: Decent Work and Economic Growth
GOAL 9: Industry, Innovation and Infrastructure
GOAL 10: Reduced Inequalities
GOAL 16: Peace, Justice and Strong Institutions