IGF 2019 WS #179 Human-centered Design and Open Data: how to improve AI

Organizer 1: Caroline Burle, Ceweb.br/NIC.br
Organizer 2: Hartmut Richard Glaser, Brazilian Internet Steering Committee - CGI.br
Organizer 3: Vagner Diniz, NIC.br - CEWEB.br
Organizer 4: Talitha Nicoletti, Pontifical Catholic University of São Paulo - PUC-SP
Organizer 5: Cappi Juliano, NIC.br
Organizer 6: Nathalia Patrício, NIC.br
Organizer 7: Mariko Kobayashi, Keio University/Mercari, Inc.

Speaker 1: Jaimie Boyd, Government, Western European and Others Group (WEOG)
Speaker 2: Karine Perset, Intergovernmental Organization, Western European and Others Group (WEOG)
Speaker 3: Diogo Cortiz da Silva, Technical Community, Latin American and Caribbean Group (GRULAC)
Speaker 4: Luciana Terceiro, Civil Society, Latin American and Caribbean Group (GRULAC)
Speaker 5: Juan Ortiz Freuler, Civil Society, Western European and Others Group (WEOG)

Policy Question(s): 

Most popular machine learning techniques are based on supervised learning and unsupervised learning approaches. In both cases, data is crucial for training the algorithms. Thus, machine Learning is leading a real data revolution. It is a sub-area of Artificial Intelligence (AI) that relies on data to identify pattern, classify, aggregate, in others words, to learn and generate values to societies.

In order to stimulate a scenario where different societies can lead the development of Artificial Intelligence (AI) the first action should be to provide access to data and ensure its quality. But this action by itself is not enough. Systems also rely on complex interactions between human and machines, and we need to embrace different methods to involve people in the process of developing an AI system to ensure a humanistic approach, since inclusion in the design process can lead to AI that is better prepared to satisfy the needs of local people. Considering this scenario, open data may also add value to this process, lowering barriers of entry to ensure the global south can participate in this new economy.

In this workshop, we propose some questions that could stimulate a interdisciplinary debate about the importance of different design approaches, such as Human-Centered Design and Interaction Design, and open data principles to address two key challenges in data governance and AI: data concentration and humanistic approach in AI.

a)What are the developmental and ethical effects of data concentration? How can technical approaches address this challenge?
b)To ensure the global south can participate in this new economy, to what extent and how can the open data agenda can contribute to ensuring equitable access to data? Is offering data under open data principles an effective strategy to achieve data quality?
c)How can we ensure AI systems don't violate people's basic rights, and how can Open Data and different design approaches, such as Human-centered and Interaction Design help to prevent this?
d)To what extent and how can different design approaches help evaluate and decide what values and priorities are programmed into the machines?
e)How the inclusion in the design process can lead to AI that is better prepared to satisfy the needs of local people?
f)Thus, how different design approaches may help to develop tools to give users the control over their own data, such as Web decentralization platforms?

Relevance to Theme: One purpose of this workshop is to discuss how different design approaches, such as Human-Centered and Interaction Design could be used to bring a humanistic approach to Artificial Intelligence and Data Governance.

A second purpose is to discuss the risks of data concentration and how open data initiatives and Web technologies can help to democratize access to key data, increasing quality and respecting privacy, one of the crucial factors for systems of machine learning.

The workshop will also discuss initiatives, technologies and design approaches for Web decentralization that are expected to give to the users the control of their personal data, and the impacts that this change may bring to governance and policies. Furthermore, the connection between Data Governance of AI, open data and control of personal data.

Relevance to Internet Governance: Data is key to promote monitoring and accountability for the UN’s 2030 Agenda for Sustainable Development, as well as to enhance its Sustainable Development Goals. Discussions around data are not only important for promoting a better world, calling for action by all countries in a global partnership, but also for every human being who has access to the Internet and is a Web user.

Although the Web began as a platform to share documents, since the early 2000's we are in the era of data on the Web. And therefore the development of the Internet and the Web technologies facilitated the so called data revolution.

The data revolution brings discussions such as ethical approaches for using data on the Web; privacy and personal data e.g. GDPR; equitable access to data; among others. Regarding all these issues, the role of different design approaches, such as Human-Centered and Interaction Design, re-decentralization of the Web and data localization is in the core of the debate. So, how do we contribute to inclusive economic development while protecting human rights?

Format: 

Debate - Classroom - 60 Min

Description: Machine Learning is leading a real data revolution. It is a sub-area of Artificial Intelligence (AI) that relies on data to identify pattern, classify, aggregate, in others words, to learn and generate values to societies. Data is the fuel for Machine Learning and the algorithms are becoming more powerful over the days. However, it is important to highlight the data is not equally available and distributed for everybody. Data may be a barrier of entry to ensure the global south can participate in this new economy. We argue that that data is being extracted from the global south and access is being monopolized by big players from the north, which is entrenching global south into a position of consumer, not producer of technology.

In this workshop, we discuss how open data principles and web technologies could help to overcome some of the consequences of this data concentration and increase its quality. We also discuss how important is to bring a humanistic approach in Artificial Intelligence. We definitely need to involve people in the process of developing new cognitive technologies in order to find real requirements, decide what values should be incorporated in the system, evaluate its results and minimize its risks. In this case, we argue that different design approaches, such as Human-Centered and Interaction Design, is a powerful approach to be incorporate in machine learning projects once it helps to focus at the technological development based on people's needs. Last but not least, we also discuss the problematic of personal data and some technical and design initiatives that could help to re-decentralize the Web and give users control over their own data. Regarding all these issues, the importance of different design approaches, the use of open data principles and Web technologies are in the core of the debate.

So, how do we contribute to inclusive economic development while attending people's need and protecting humans right? This emerging question will guide our workshop and it is the inspiration for all the policy questions detailed in the previous section. It will also give us theoretical and practical background to rethink aspects of data governance, data quality and AI development in order to be prepare us for immediate future.

Workshop agenda
1) Opening remarks on policies and practices regarding data governance and artificial intelligence by the moderator of the workshop (5 min)
2) Five interventions with use cases to generate the debate among the speakers and the audience about the importance of open data and different design approaches for data governance and Artificial Intelligence (20 minutes)
3) Experts and the audience will debate focusing on the development of a roadmap to address possible strategies for the data concentration and humanistic approach in AI (20min).
4) Closure by the moderator of the workshop (5 min)

Expected Outcomes: During the session, regarding the Policy Questions, the experts will briefly explore the concepts of different design approaches, such as Human-Centered and Interaction Design, and Open Data principles to answer the question of how they could improve Artificial Intelligence.

Use cases will be discussed among the participants and they will also discuss the challenges to improve AI through a roadmap development for the next years and how it will bring a significant change to the Web as we know it.

Hence, the workshop may provide a roadmap agreed among workshop participants to open a global debate on the core challenges to enhance AI and inclusive economic development while protecting the rights of people. The purpose of the workshop is to reach out to different stakeholders in order to disseminate this roadmap.

Onsite Moderator: 

Cappi Juliano, Technical Community, Latin American and Caribbean Group (GRULAC)

Online Moderator: 

Mariko Kobayashi, Private Sector, Asia-Pacific Group

Rapporteur: 

Nathalia Patrício, Technical Community, Latin American and Caribbean Group (GRULAC)

Discussion Facilitation: 

We will encourage the debate among experts and the audience.

Workshop agenda
1) Opening remarks on policies and practices regarding data governance and artificial intelligence by the moderator of the workshop (5 min)
2) Five interventions with use cases to generate the debate among the speakers and the audience about the importance of open data and different design approaches for data governance and Artificial Intelligence (20 minutes)
3) Experts and the audience will debate focusing on the development of a roadmap to address possible strategies for the data concentration and humanistic approach in AI (20min).
4) Closure by the moderator of the workshop (5 min)

Online Participation: 

The online moderator will manage the interaction between online participants and onsite attendees

SDGs: 

GOAL 4: Quality Education
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