Hardware is an AI Ethics Problem: Expert Visions for a Sustainable and Equitable Semiconductor Industry

Technical Summary: Hardware is an AI Ethics Problem: Expert Visions for a Sustainable and Equitable Semiconductor Industry

Problem Statement
The semiconductor industry serves as the physical foundation for contemporary AI systems, yet its governance is increasingly shaped by critical social, environmental, and geopolitical challenges that are often examined in disciplinary isolation. Prior research has addressed discrete issues—ranging from material extraction and fabrication impacts to logistics and policy—without adequately treating them as interconnected socio-technical tensions. Furthermore, while AI ethics research has expanded to cover models and data, it frequently overlooks the upstream hardware infrastructures that determine fairness, sustainability, and global access before a model is even trained. This paper identifies a gap in understanding the semiconductor supply chain through an integrative, cross-disciplinary lens that connects present frictions to normative goals.

Methodology
To address this gap, the authors conducted a two-day, in-person, participatory futuring workshop in early 2025. The study engaged 18 experts from academia (N=5), industry (N=9), and policy sectors (N=4), representing a range of professional perspectives within the semiconductor and ethical ecosystems. The workshop utilized a guided participatory approach grounded in reflective design principles and futuring methodologies.

The process involved six structured activities over two days:

1. Supply Chain Mapping: Participants mapped actions, challenges, and stakeholders across pre-selected supply chain stages to form "trios" of action–challenge–stakeholders.
2. Risk Assessment: A structured Likelihood vs. Severity Matrix was used to assess the probability and impact of identified risks.
3. Recommendation Co-design: Participants formulated actionable recommendations specifying desired outcomes, responsible actors, and concrete actions, drawing on Outcome Mapping principles.
4. Future Visions: Collaborative envisioning of future scenarios for the industry in 2030 and beyond.
5. Ideal Future Scenarios: Analysis of these visions using a simplified STEEPLE (Social, Technological, Economic, Environmental, Political, Legal, Ethical) framework.
6. Measures for Implementation: Identification of stakeholder-specific measures to realize the envisioned futures.

Qualitative data from worksheets and observer notes were analyzed using an iterative coding process (Initial/Open Coding), resulting in the synthesis of nine challenge domains and eleven recommendation categories.

Key Contributions
The paper makes five primary contributions to the discourse on AI ethics and semiconductor governance:

1. From Isolated Challenges to Interconnected Tensions: The study moves beyond fragmented treatments to demonstrate that semiconductor challenges are structurally interdependent. It articulates three central socio-technical tension pathways:
   • Sovereignty–Sustainability Tension: National protectionism and the pursuit of technological sovereignty (e.g., via export controls and domestic manufacturing mandates) undermine global sustainability goals by multiplying resource footprints and fragmenting global markets.
   • Supply Chain Opacity: The lack of traceability, often legally enforced through trade secrets and non-disclosure agreements, shields labor and environmental harms from accountability.
   • Knowledge Divide: High capital expenditures (CAPEX) and export restrictions structurally exclude smaller economies and the Global South from shaping the AI future, reinforcing colonial dynamics of resource extraction and technological dependency.
2. Cross-Disciplinary Synthesis: The paper initiates a dialogue by grounding its analysis simultaneously in the perspectives of academia, industry, and policy, offering an integrated account of systemic risk that cuts across traditional sectoral boundaries.
3. Framework for Structural Intervention: The authors synthesize participant outputs into three domains of intervention that move beyond voluntary Corporate Social Responsibility (CSR):
   • Radical Visibility: Shifting from voluntary disclosure to enforceable transparency mechanisms.
   • Strategic Interdependence: Replacing isolationism with governance models that balance local resilience with global cooperation.
   • Epistemic Redistribution: Treating semiconductor expertise as a public good requiring active redistribution to democratize access.
4. Normative Pathways for Anticipatory Governance: The study details specific governance, technological, and social shifts required to bridge the gap between current frictions and ideal futures, contrasting the risks of a "Rebound Effect" with a vision of "Sustainable Cooperation."
5. Semiconductor Governance as a First-Order Ethical Concern: The paper argues that AI ethics must extend beyond algorithms to encompass the hardware layer, where questions of fairness and sustainability are determined long before model deployment.

Results
The workshop identified nine interconnected challenge domains, including environmental constraints, facility migration, transparency deficits, industrial espionage, education gaps, competitive barriers, governance failures, human rights violations, and external influences.

Participants envisioned ideal futures centered on interdependence and inclusive access. Key proposed measures include:

• The CO2/Emisions Semaphore: A standardized traffic-light labeling system (Green-Red, A-E) for semiconductor and electronic devices to inform buyers of production footprints, similar to the Nutri-Score in food. This aims to translate technical data into public accountability.
• Strategic Interdependence: Establishing peace agreements and memoranda of collaboration between regions (e.g., EU-Taiwan) and adopting a "One Voice" strategy for Europe to enforce shared regulatory frameworks.
• Epistemic Redistribution: Implementing funding calls to transfer know-how from leading regions to emerging ecosystems, lowering barriers to entry, and optimizing labor laws across borders to safeguard human rights.

Significance and Claims
The paper claims that the challenges of the semiconductor industry cannot be understood in isolation; they are constitutive of AI itself. The authors argue that without embedding ethics and sustainability into frameworks like the EU Chips Act or the U.S. CHIPS and Science Act, efforts to reduce supply chain risks will merely relocate carbon footprints and labor precarity.

The study posits that participatory methods can transform fragmented debates into coherent pathways for accountable, anticipatory governance. By connecting algorithmic concerns to material infrastructures, the authors call on the AI ethics community to treat hardware governance not as background infrastructure, but as a foundational site of ethical inquiry. The paper concludes that resilience requires transparency, that ethics and sustainability are inseparable from competitiveness, and that global cooperation must be balanced with local empowerment to ensure access to digital infrastructure is treated as a social good.

Note: The paper acknowledges limitations regarding the demographic diversity of participants (predominantly European) and the strategic rather than operational nature of the two-day workshop outputs. It suggests future work should focus on translating these recommendations into operational frameworks and expanding participation to include upstream workers and communities in the Global South.