Research AI Consciousness Claims → Generate Risk Assessment → Update Policies
Systematically evaluate AI consciousness claims from vendors, assess risks to your AI strategy, and update internal AI governance policies accordingly.
Workflow Steps
Perplexity
Deep research on consciousness claims
Use Perplexity to research specific claims about AI consciousness from vendors you use or are considering. Include scientific consensus, expert opinions, and regulatory implications.
ChatGPT
Generate risk assessment framework
Prompt ChatGPT to create a structured risk assessment template covering legal, ethical, PR, and operational risks of using AI systems with consciousness claims.
Airtable
Track vendor consciousness positions
Build a database tracking each AI vendor's public positions on consciousness, model welfare, and ethical AI. Include risk scores and policy implications.
Google Docs
Update AI governance policies
Use research findings to update internal AI usage policies, vendor selection criteria, and ethics guidelines. Include specific language about consciousness claims and model welfare considerations.
Microsoft Teams
Present findings to governance committee
Schedule governance committee meeting to review findings, discuss policy updates, and get approval for any changes to AI vendor relationships or usage policies.
Workflow Flow
Step 1
Perplexity
Deep research on consciousness claims
Step 2
ChatGPT
Generate risk assessment framework
Step 3
Airtable
Track vendor consciousness positions
Step 4
Google Docs
Update AI governance policies
Step 5
Microsoft Teams
Present findings to governance committee
Why This Works
Creates a systematic approach to evaluate evolving AI consciousness claims, helping organizations make informed decisions about AI adoption while managing reputational and regulatory risks
Best For
Enterprise risk management for organizations heavily using AI tools, especially in sensitive industries like healthcare, finance, or legal
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