Best Ethical AI Practices for Telecommunications

This new white paper "Introduction to AI assurance" by the UK Department for Science, Innovation, and Technology from Feb 12, 2024, provides an EXCELLENT overview of assurance methods and international technical standards that can be utilized to create and implement ethical AI systems. The new guidance is based on the UK AI governance framework, laid out in the 2023 white paper "A pro-innovation approach to AI regulation". This white paper defined 5 universal principles applicable across various sectors to guide and shape the responsible development and utilization of AI technologies throughout the economy: - Safety, Security, and Robustness - Appropriate Transparency and Explainability - Fairness - Accountability and Governance - Contestability and Redress The 2023 white paper also introduced a suite of tools designed to aid organizations in understanding "how" these outcomes can be achieved in practice, emphasizing tools for trustworthy AI, including assurance mechanisms and global technical standards. See: https://lnkd.in/gydvi9Tt The new publication, "Introduction to AI assurance," is a deep dive into these assurance mechanisms and standards. AI assurance encompasses a spectrum of techniques for evaluating AI systems throughout their lifecycle. These range from qualitative assessments for evaluating potential risks and societal impacts to quantitative assessments for measuring performance and legal compliance. Key techniques include: - Risk Assessment: Identifies potential risks like bias, privacy, misuse of technology, and reputational damage. - Impact Assessment: Anticipates broader effects on the environment, human rights, and data protection. - Bias Audit: Examines data and outcomes for unfair biases. - Compliance Audit: Reviews adherence to policies, regulations, and legal requirements. - Conformity Assessment: Verifies if a system meets required standards, often through performance testing. - Formal Verification: Uses mathematical methods to confirm if a system satisfies specific criteria. The white paper also explains how organizations in the UK can ensure their AI systems are responsibly governed, risk-assessed, and compliant with regulations: 1.) For demonstrating good internal governance processes around AI, a conformity assessment against standards like ISO/IEC 42001 (AI Management System) is recommended. 2.) To understand the potential risks of AI systems being acquired, an algorithmic impact assessment by a accredited conformity assessment body is advised. This involves (self) assessment against a proprietary framework or responsible AI toolkit. 3.) Ensuring AI systems adhere to existing data protection regulations involves a compliance audit by a third-party assurance provider. This white paper also has exceptional infographics! Pls, check it out, and TY Victoria Beckman for posting and providing us with great updates as always!

As Prezent’s founder, I’ve seen first-hand how AI is changing the way we make decisions— It can make the process *much* faster and smarter. There is a lot of skepticism and mistrust around AI though… And rightfully so! Poorly built or managed AI can lead to ⤵ → Unfair treatment → Privacy concerns → No accountability (and more) So, here’s our approach toward ethical AI at Prezent: 1️⃣ Keeping data secure Your data's sacred. We're strict about protecting it, following laws like GDPR and CCPA. Privacy isn't a bonus — it's a baseline. 2️⃣ Putting fairness first Bias has no place here— We're on a mission to find and reduce biases in AI algorithms to make decisions fair for all… no picking favorites. 3️⃣ Being transparent AI shouldn't be a secret black box. We clearly explain how ours works and the decisions it makes. ↳ Openness → Trust among users 4️⃣ Monitoring often Keeping AI ethical isn't a one-and-done deal — it's an ongoing commitment. That said, We're always looking out for issues… Ready to adjust as necessary and make things better. 5️⃣ Engaging all stakeholders AI affects us all, so we bring *everyone* into the conversation. ↳ More voices + perspectives → Better, fairer AI 6️⃣ Helping humans We build AI to *help* people, not harm them— This means putting human values, well-being, and sustainability first in our actions and discussions. 7️⃣ Managing risk We're always on guard against anything that might go wrong… …from privacy breaches to biases. This keeps everyone safe. 8️⃣ Giving people data control Our systems make sure you're always in the driver's seat with your personal information. Your data, your control— Simple as that. 9️⃣ Ensuring data quality Great decisions *need* great data to back them up— So, our QA team works hard to ensure our AI is trained on diverse and accurate data. 🔟 Keeping data clean We’re serious about keeping our data clean and clear— Because well-labeled data → Better decisions In fact, it’s the *foundation* for developing trustworthy, unbiased AI. Truth is, getting AI ethics right is tough. But compromising our principles isn’t an option— The stakes are *too* high. Prezent’s goal? ↳ To lead in creating AI that respects human rights and serves the common good. Settling for less? Not in our DNA.

AI regulatory frameworks are cropping up across regions, but it's not enough. So far, we've seen: - EU’s Artificial Intelligence Act: Setting a global precedent, the EU's draft AI Act focuses on security, transparency, and accountability. - U.S. AI Executive Order by Biden Administration: Shares strategies for AI, emphasizing safety, privacy, equity, and innovation. - Japan's Social Principles of Human-Centric AI: Japan emphasizes flexibility and societal impact in their AI approach. - ISO's Global Blueprint: ISO/IEC 23053:2022/AWI Amd 1 aims to standardize AI systems using machine learning worldwide. - IAPP's Governance Center: Leading in training professionals for intricate AI regulation and policy management. But these are just the beginning, a starting point for all of us. Ethical AI usage goes beyond regulations; it's about integrating ethical considerations into every stage of AI development and deployment. Here’s how YOU, as an in-house counsel, can ensure ethical AI usage in your company, specifically when it comes to product development: - Always disclose how AI systems make decisions. This clarity helps build trust and accountability - Regularly audit AI systems for biases. Diverse data and perspectives are essential to reduce unintentional bias - Stay informed about emerging ethical concerns and adjust practices accordingly - Involve a range of stakeholders, including those who might be impacted by AI, in decision-making processes - Invest in training for teams. Understanding ethical implications should be as fundamental as technical skills The collective global efforts in AI regulation, like those from the US, EU, Japan, ISO, and IAPP, lay the foundation. However, it's our daily commitment to ethical AI practices that will truly harness its potential while ensuring that AI serves humanity, not the other way around. #AIRegulations #AIUse #AIEthics #SpotDraftRewind