Human Capacity-Centered Algorithms

The session explores algorithmic categorizations through the lens of designated groups, individuals with facial asymmetry, different gestures, gesticulation, communication, speech and action patterns, including groups with impairments and disabilities, approaches to human-centricity and safety.

AI Policy and Eurasian/Transatlantic Safety Dialogue

The session explore existing challenges and solutions for AI policy and safety treaties, high and unacceptable risks systems through the lens of designated and vulnerabled groups. It addresses misuse and silos including categories of algorithms and public systems, proposed actions and criteria.

Algorithmic Diversity - Neurodiversity Inclusive AI & Human Rights

During the live session, we will dive into the meaning and application of algorithmic diversity in technology (including such cases as neurodiversity). Using the latest experiences, cases and research, we will analyze the current state and problems of inclusive innovation and technology, including the problems of representation and criteria, inclusive research and design-thinking, the building of inclusive products (AI-driven platforms, devices, apps, social and emotional robotics), ethical considerations and concerns (the "black-box" and "double-check" problems, transparency, explainability, fairness, surveillance), shortcomings of current technology ecosystems, policies and human rights frameworks.

Algorithmic Diversity - Disability Inclusive AI & Human Rights

Applying a disability equity lens to the ML pipeline. Algorithms can perpetuate societal inequities and cultural prejudices. Bias can enter at different stages due to: Priorities that do not include (dis)ability equity considerations Organizational structure, unconscious and conscious bias from the team developing the algorithm.

Accessible Nations, Policies & Human RIghts Framework

At least 1 in 6 people living with one or more neurological conditions, 1 in 7 are neurodivergent, 1 in 4 adults — suffers from a diagnosable mental disorder in a given year. All of these differences are connected to the spectrum of ability and comorbidity, sensibility, physical and tactile experiences, visual and color experiences, differences in the systems of learning, memorizing, systemizing, and empathizing. These “invisible disabilities” lead to the biggest level of social exclusion, isolation and rejection across all conditions and states. Unemployment among those with autism is approximately 85%, severe mental health disorders – 68%-83%, Down syndrome – 43%. Social, economic and environmental parameters add even more criteria to this analysis that are distributed across different social layers, subgroups, communities.

How can nations, cities and ecosystems embrace human-centered algorithms, environments, policy and emerging technology – specifically addressing human capability, wellbeing, experiences and beyond?