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AI and Identity

Sri Yash Tadimalla, Mary Lou Maher

TL;DR

The paper addresses the AI divide and diversity gaps by proposing the AI Identity framework to map how creators, creations, and consequences shape AI's social embedding. It defines AI Identity in internal and external dimensions and analyzes how identities of developers, data, and governance influence AI systems, advocating for inclusive, human-centered design. By detailing an infrastructure–technical–socio-technical stack and a framework that foregrounds diversity, fairness, and accountability, the work reveals how bias can propagate across layers and how governance can mitigate harms. The proposed framework provides actionable guidance for researchers, educators, policymakers, and industry to broaden participation and align AI with societal values.

Abstract

AI-empowered technologies' impact on the world is undeniable, reshaping industries, revolutionizing how humans interact with technology, transforming educational paradigms, and redefining social codes. However, this rapid growth is accompanied by two notable challenges: a lack of diversity within the AI field and a widening AI divide. In this context, This paper examines the intersection of AI and identity as a pathway to understand biases, inequalities, and ethical considerations in AI development and deployment. We present a multifaceted definition of AI identity, which encompasses its creators, applications, and their broader impacts. Understanding AI's identity involves understanding the associations between the individuals involved in AI's development, the technologies produced, and the social, ethical, and psychological implications. After exploring the AI identity ecosystem and its societal dynamics, We propose a framework that highlights the need for diversity in AI across three dimensions: Creators, Creations, and Consequences through the lens of identity. This paper proposes the need for a comprehensive approach to fostering a more inclusive and responsible AI ecosystem through the lens of identity.

AI and Identity

TL;DR

The paper addresses the AI divide and diversity gaps by proposing the AI Identity framework to map how creators, creations, and consequences shape AI's social embedding. It defines AI Identity in internal and external dimensions and analyzes how identities of developers, data, and governance influence AI systems, advocating for inclusive, human-centered design. By detailing an infrastructure–technical–socio-technical stack and a framework that foregrounds diversity, fairness, and accountability, the work reveals how bias can propagate across layers and how governance can mitigate harms. The proposed framework provides actionable guidance for researchers, educators, policymakers, and industry to broaden participation and align AI with societal values.

Abstract

AI-empowered technologies' impact on the world is undeniable, reshaping industries, revolutionizing how humans interact with technology, transforming educational paradigms, and redefining social codes. However, this rapid growth is accompanied by two notable challenges: a lack of diversity within the AI field and a widening AI divide. In this context, This paper examines the intersection of AI and identity as a pathway to understand biases, inequalities, and ethical considerations in AI development and deployment. We present a multifaceted definition of AI identity, which encompasses its creators, applications, and their broader impacts. Understanding AI's identity involves understanding the associations between the individuals involved in AI's development, the technologies produced, and the social, ethical, and psychological implications. After exploring the AI identity ecosystem and its societal dynamics, We propose a framework that highlights the need for diversity in AI across three dimensions: Creators, Creations, and Consequences through the lens of identity. This paper proposes the need for a comprehensive approach to fostering a more inclusive and responsible AI ecosystem through the lens of identity.
Paper Structure (11 sections, 4 figures)

This paper contains 11 sections, 4 figures.

Figures (4)

  • Figure 1: Representation of global workforce and AI industry impact
  • Figure 2: The AI Identity Research Framework
  • Figure 3: The AI Identity Ecosystem
  • Figure 4: The AI Identity Framework