Explores the frameworks, policies, and strategies that guide the ethical development, deployment, and regulation of AI systems. This category covers governance models, compliance standards, regulatory challenges, and the role of oversight in ensuring responsible AI use across industries.
Reflecting on the United Nations Foundation Science Summit 2024, one thing is clear: We are at a pivotal moment in humanity’s relationship with AI. The summit addressed a key issue: how to govern a technology that blurs the line between humans and machines. The Challenge of AI Governance The UN report “Governing AI for Humanity” […]
Read More… from AI Governance: UN Summit Insights on Ethical Tech Future
The UN Science Summit is sparking crucial conversations about the future of AI.
AI’s potential is immense, but are we prepared to navigate its ethical challenges?
Key takeaways from the summit so far:
The urgent need for culturally sensitive AI
The complex debate on data sovereignty
The importance of ethical frameworks
Read the full article to learn more about these critical insights and their implications for the future of AI. […]
I attended the recent SHARE Association conference as a first-time Tech Field Day delegate (#TFDx), which allowed me to see various mainframe modernization strategies. BMC Software’s presentation at #TFDx was a highlight. It addressed the fear of change, a key barrier to modernization.As a former COBOL programmer who transitioned into AI ethics, I bring a […]
Read More… from COBOL to AI: Conquering Mainframe Modernization Fears
Transparency and accountability are not just buzzwords, but essential pillars for establishing trust in AI systems as they increasingly become integrated into decision-making processes. It is vital to ensure that these systems can be explained and that clear responsibility for their outcomes is defined. This installment of our series delves into why transparency and accountability […]
