Last month, we convened dinners in both Melbourne and Sydney, uniting leaders in Product and Technology.
The focus? The immense potential and ethical implications of generative AI. The enthusiasm was palpable, but it was matched by serious discussions on the ethical dimensions of AI.
For instance, consider the potential of Chat GPT in streamlining internal investigations.
Upload all the documentation, synthesise and generate a recommendation. Sounds productive in theory, but would it be fair, would context be factored in and could you trace back to evidence?
While the efficiency gains are impressive, questions around fairness, context, and traceability remain unresolved and critical.
Towards Trustworthy AI
In 2018, the High-Level Expert Group on AI in Europe established a set of guidelines aimed at ethical and lawful AI deployment. Updated in 2021, these guidelines have crystallised into seven core requirements for "Trustworthy AI":
- Human Agency and Oversight
- Technical Robustness
- Data Governance
- Transparency
- Diversity and Fairness
- Societal and Environmental Well-being
- Accountability
Innovations in Traceability
The complexity of this subject is not easily distilled into a single post. However, emerging tools like the Web Search AI Plugin and PortfolioPilot Plugin offer mechanisms for enhanced traceability and real-time data access.
In conclusion, the key lies in achieving a balanced approach: leveraging AI's transformative capabilities while maintaining a steadfast commitment to ethical, transparent, and secure practices. The journey is as crucial as the destination in shaping a responsible AI landscape.
#AI #EthicalAI #TrustworthyAI #GenerativeAI #Innovation
