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Thursday, November 28 • 10:35 - 11:35
WS 179 Human-centered Design and Open Data: How to Improve AI

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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.

Questions to 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:

  1. What are the developmental and ethical effects of data concentration? How can technical approaches address this challenge?
  2. 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?
  3. 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?
  4. To what extent and how can different design approaches help evaluate and decide what values and priorities are programmed into the machines?
  5. How the inclusion in the design process can lead to AI that is better prepared to satisfy the needs of local people?
  6. Thus, how different design approaches may help to develop tools to give users the control over their own data, such as Web decentralization platforms?

Workshop agenda

  • Opening remarks on policies and practices regarding data governance and artificial intelligence by the moderator of the workshop (5 min)
  • 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)
  • 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).
  • Closure by the moderator of the workshop (5 min)


Diogo Cortiz da Silva, Technical Community, Latin American and Caribbean Group (GRULAC)
Heloisa Candello, Private Sector, IBM Research Lab - Brazil
Jaimie Boyd
, Government, Western European and Others Group (WEOG) - remote participation
Krzysztof Izdebski, Civil Society, Western European and Others Group (WEOG)
Luis Aranda
, Intergovernmental Organization, Western European and Others Group (WEOG)

Onsite Moderator 
Vagner Diniz
, Technical Community, Latin American and Caribbean Group (GRULAC) 

Online Moderator

Mariko Kobayashi, Private Sector, Asia-Pacific Group 

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

Session Organizers
avatar for Caroline Burle

Caroline Burle

Responsável por Relações Institucionais e Internacionais, Ceweb.br / Nic.br
Responsável pelas Relações Institucionais do Centro de Estudos sobre Tecnologias Web (Ceweb.br) e do W3C Brasil. É especialista em Negociação pela Fundação Getúlio Vargas e Mestre em Relações Internacionais pelo San Tiago Dantas. É integrante do Núcleo de Estudos e Análises... Read More →

Thursday November 28, 2019 10:35 - 11:35 CET
Raum II