1. Big Data, Algorithmic Bias, Discrimination:

– Factors leading to a bias in algorithms and big data 

– Approaches and methods that can be used to address these possible biases 

– Case studies of algorithmic bias and its impact on the marginalised communities? 

– Role of stakeholders in addressing these potential biases 

  1. Representative and Ethical AI Development:

– Role of stakeholders in the ethical development of AI 

– Approaches and frameworks to address the issues of algorithmic opacity and algorithmic accountability  

– Ways to mainstream the needs of the community in designing AI innovations 

– Safeguards required for the protection of individuals from the newer forms of threats emerging from AI usage 

  1. AI Access and Meaningful Connectivity:

– Role of stakeholders in building AI literacy and ensuring affordable AI for all 

– Contribution of digital public infrastructure in improving AI access 

– Approaches to mainstream principles of non-discrimination and equal access in AI  

  1. AI, Workers, and Platform Economies:

– Risks emerging from the integration of AI in platform economies 

– Strategies to promote worker rights in the context of AI usage in platform economies 

– AI-driven management and advocacy for better working conditions for workers  

– Data transparency frameworks for consumers and workers in platform economies 

  1. AI Regulation and Citizen-Centric Governance:

– Designing AI policy and governance to address diverse perspectives, particularly of the Global South 

– Role of contextualising and localising community needs in designing AI regulations and policy 

– Role of bottom-up approaches for designing community-centric AI governance 

  1. AI, Misinformation, and Disinformation:

– Role of AI in the disseminating and controlling the spread of online misinformation 

– Impact of AI-generated misinformation on democracy and public institutes 

– Role of AI in differentiating between authentic sources of information and misinformation 

  1. Data Citizenship and Community Making:

– Role of citizens in  promoting data-driven governance and decision-making 

– Ethical considerations for storing, collecting, and using personal data 

– Initiatives to promote diversity and representation in data 

– Measures by individuals and communities in the context of excessive data collection 

  1. Online Privacy, Security, and Data Rights:

– What are some key challenges individuals face in protecting their online data? 

– What legal frameworks will support the communities in maintaining their online privacy and data 

rights? 

– How can AI Algorithms impact the privacy and security of individuals? 

  1. The Absent Data:

– Impact of algorithms and big data on community knowledge 

– Influence of absent data on algorithm design and AI decision-making processes 

– Ethical considerations in providing AI access for all, especially marginalised populations 

  1. AI and Environment:

– Role of AI in advancing climate mitigation efforts 

– Contribution of AI in the exploitation of the environment and natural resources 

– Frameworks and approaches to assess the carbon footprint of big data sets and training AI algorithm