Toward trustworthy AI systems: addressing safety, ethics, and governance

Artificial intelligence has the potential to transform society in countless beneficial ways, but with growing power and complexity also comes an array of challenges requiring thoughtful solutions. From issues of bias to job displacement, transparency to responsible usage policies, today’s state-of-the-art #AI systems surface many open questions and problematic aspects still being grappled with. Until these concerns are meaningfully addressed through interdisciplinary collaboration, AI risks contributing to rising inequality, discrimination, unemployment, safety risks and erosion of civil rights rather than serving inclusively in the public interest.

Here I outline key specific problematics that researchers, policymakers, companies and the wider public must turn focused attention toward resolving to ensure our AI-integrated future is one of empowerment rather than destabilization.

Key AI Problematics

AI Safety: ensuring AI systems behave safely, avoid harm, and are securely contained even as they become more powerful and autonomous. Issues around accident risk, embedded biases, hacking vulnerabilities, and uncontrolled self-improvement.

Job Displacement: AI automation may disrupt job markets and entire industries faster than displaced workers can adapt and be re-trained. It could increase wealth inequality, unemployment, and destabilize economies.

Bias and Fairness: pattern recognition AI relies on data and statistical correlations that can embed societal biases around race, gender, age, abilities, etc. perpetuating discrimination through automated decisions. Achieving fair, accountable, and transparent AI remains challenging.

Transparency and explainability: the complex inner workings of many AI models are black boxes even to their creators, lacking model transparency and explainability. This makes auditing for issues like bias and safety very difficult while facing public distrust.

AI Misuse: AI could expand capabilities for surveillance, persuasion tactics, asymmetric cyberwarfare, autonomous weapons, technology-fueled oppression, and other concerning applications lacking oversight.

Legal and Ethical Grays: sophisticated AI gives rise to many open questions around accountability, liability, privacy, informed consent, manipulation, nudging of human behavior, and more with unclear regulatory guidance on what constitutes ethical AI design and use.

Data Governance Difficulties: vast troves of data are required to train powerful AI models. Poor governance risks privacy violations, tightly held concentrations of data power, and marginalization of vulnerable groups not well-represented in datasets.

Sophisticated systems demand sophisticated safeguards. An unprepared embrace of AI, however dazzling its results, practically ensures we will encode our biases into these technologies and entrench disparities as a result. Progress and inclusion must advance hand-in-hand.

I aimed to introduce the idea that while AI holds great promise, focused efforts to address its many open challenges and risks are critical as well. The bullet points of issues act as a starting landscape of the “hard problems” needing solutions for AI to integrate safely and positively into society.