Data & Society

The Formalization of Social Precarities podcast explores platformization from the point of view of precarious gig workers in the Majority World. This conversation was moderated by Aiha Nguyen and Murali Shanmugavelan featuring the voices of Ambika Tandon, Ludmilla Costhek Abílio, and Ananya Raihan. You will also be hearing the experience of two platform workers interviewed for this project: Fatema Begum from Bangladesh and Nicolas Sauza from Brazil. Their voices are narrated in English by Data & Society staff members Iretiolu Akinrinade and Rigoberto Lara Guzmán, respectively. This podcast was edited by Sam Grant.

Data & Society’s report, Doing the Work: Therapeutic Labor, Teletherapy, and the Platformization of Mental Health Care, written by Livia Garofalo, explores how these new arrangements of therapeutic labor are affecting how therapists provide care and make a living in the US. By focusing on the experiences of providers who practice teletherapy and work for digital platforms, our research examines the fundamental tensions that emerge when a profession rooted in clinical expertise, licensing, and training standards meets the dynamics of platformization, productivity incentives, and algorithmic management. In this conversation, we reflected on how technology is changing the conditions of how therapists do their work, on the consequences for the present and future of therapeutic labor, and on how this might be changing our understanding of therapy itself.

The podcast delves into the labor impacts of generative AI, discussing its influence on education, therapy, and various industries. It highlights concerns about bias in AI systems and the importance of establishing guidelines in education. The conversation also explores the challenges of automating tasks involving ethics and privacy, emphasizing the need for regulations and ethical evaluations.

Experts from the Trustworthy Infrastructures program discuss the impact of AI systems on trust within marginalized groups. Topics include challenges of discerning between human and AI-generated content, evaluating AI systems, biases in natural language processing, struggles for accurate representation in AI technologies, and building trust and representation within marginalized communities.

Explore the impact of data systems on queer subjects and strategies of resistance. Delve into LGBTQ activism, alternative models for privacy, and shared vulnerability in queer data practices. Discuss the concept of algorithms shaping identities, algorithmic oppression, and queer resistance in technology. Dive into visual representation in queer history and the power of queer information activism in reshaping narratives.

Generative AI has seeped into many corners of our lives, and threatens to upend the economy as we know it, from education to the film industry. How do workers’ encounters with it differ from their experiences with other systems of automation? How are they similar, and how might this help us understand the shape and stakes of this latest technology?In this three-part Databite series, Data & Society’s Labor Futures program brings together creators, platform workers, call center workers, coders, therapists, and performers for conversations with technologists, researchers, journalists, and economists to complicate the story of generative AI. By centering workers’ experiences and interrogating the relationship between generative AI and underexplored issues of hierarchy, recognition, and adaptation in labor, these interdisciplinary conversations will uncover how new technological systems are impacting worker agency and power.Learn more about the speakers, series, and references at datasociety.net.

Explore the impact of generative AI on labor, including hierarchies, power asymmetries, and low wages. Discuss the increasing demand for professionals and concerns over copyright infringement. Introduce John Lopez and recommend experts on AI and image generators. Highlight the importance of including worker voices in AI discussions and advocating for transparency. Examine the labor impacts of generative AI and audience appreciation of AI-generated content.

Tamara Kneese and Tonia Sutherland discuss caring for digital remains and online legacies after death. They explore the challenges of preserving digital remains attached to corporate platforms. The podcast also delves into the intersection of technology and death on the internet, the relevance of historical analog records, and the importance of caring for someone's digital possessions after their death. The speakers touch on the use of images of black death in public conversation and the historical use of photography by black political agitators.

An analysis of the recently released AI executive order by the Biden administration and its implications for AI governance and accountability. The challenges in implementing the order, including the appointment of a chief AI officer and improving transparency of AI use cases in government. The impact of the order on AI practices in the government and private sector, and the lack of guidance on federal grants for surveillance technology.

As AI presents technical and engineering innovations, the systems present fundamental risks to people, their families, and their communities. Public participation in AI will not be easy. But there are foundational lessons to apply from other domains. Author and legal scholar Michele Gilman’s latest policy brief, Democratizing AI: Principles for Meaningful Public Participation, builds on a comprehensive review of evidence from public participation efforts in anti-poverty programs and environmental policy that summarizes evidence-based recommendations for how to better structure public participation processes for AI. To discuss the policy brief, we invited Michele Gilman to be in conversation with Harini Suresh, Assistant Professor of Computer Science at Brown University, and Richard Wingfield, Director of Technology and Human Rights at BSR. This conversation was moderated by D&S Participatory Methods Researcher, Meg Young, and D&S Policy Director, Brian Chen.