The AI Ethics Brief #179: Seen, But Not Heard: AI's Impact On Labour

2024-10-01 · Source: The AI Ethics Brief · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Legal & Regulatory, Government & Public Sector · Depth: Intermediate, medium

Summary

The AI Ethics Brief, a bi-weekly publication by the Montreal AI Ethics Institute, highlights key developments in AI ethics, focusing on sectoral applications and regulatory efforts. Part III of the "State of AI Ethics Report" (SAIER) examines AI's impact across healthcare, education, oil and gas, and the arts, detailing risks like patient privacy erosion from "digital twins" and the undermining of creative work by generative AI. Concurrently, Brazil's proposed AI regulation (PL 2338/2023) aims to govern "excessively risky" and "high-risk" AI systems, with provisions for artists and creatives whose work is used without consent or compensation. Both discussions underscore the growing importance of collective action and worker-first approaches, exemplified by trade unions and professional bodies advocating for ethical AI deployment and accountability across various industries.

Key takeaway

For CTOs and VPs of Engineering evaluating AI deployments, you should prioritize ethical considerations and worker engagement from the outset. Your teams must integrate robust governance frameworks, like those proposed in Brazil's bill, to address "high-risk" systems and protect employee and user rights, especially regarding data privacy and intellectual property. Proactive consultation with employees and adherence to principles of consent and compensation will mitigate risks of disillusionment and legal challenges.

Key insights

AI adoption across sectors necessitates robust ethical frameworks and worker-centric governance to mitigate negative impacts.

Principles

• Prioritize patient privacy over computational data.
• Preserve critical thinking in educational settings.
• Ensure consent, compensation, and control for creative works.

Method

Brazil's PL 2338/2023 establishes rules for "excessively risky" and "high-risk" AI systems, promoting transparency and accountability through citizen oversight and specific provisions for artists.

In practice

• Consult employees early in AI procurement processes.
• Implement collective licensing agreements for AI-generated content.
• Utilize frameworks like SOBIRTECH for biometric identifier verification.

Topics

• AI Ethics
• AI Regulation
• Sectoral AI Applications
• Generative AI
• Worker Rights

Best for: CTO, VP of Engineering/Data, Director of AI/ML, AI Ethicist, Policy Maker, Business Analyst

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Editorial summary, takeaway, and curation by AIssential. Original article published by The AI Ethics Brief.