Trusting AI (Even When It’s Not Perfect)
There’s a lot of talk about trusting AI these days and rightly so. We’re putting these systems into decisions that matter: healthcare, hiring, pricing, customer service, even policing. When something goes wrong, we ask: Can I really trust AI to get this right? But underneath that question is a tougher one: Do I trust anything […]
Making Sense of Context: What It Is, Where It Comes From, and Why It Matters
In any intelligent system, especially those that adapt, respond, or reason, context is everything. It shapes what a system knows, how it interprets input, what decisions it makes, and how it interacts with users. But “context” is one of those overloaded words we all use without always unpacking what we mean. In a previous article, […]
Transparency by Role: Need to Know, Allowed to Know, and Able to Understand
A view of transparency that I keep coming back to is the role of the user from both a data governance perspective, as well as from a comprehension perspective. Different users bring different responsibilities, goals, and levels of context. That means transparency can’t be flat or uniform. It needs to adapt. There are three dimensions […]
When AI Forgets the Bigger Picture: The Context Challenge
Everyone’s talking about the latest models, the biggest context windows, the newest breakthroughs. But here’s what rarely gets mentioned: many AI implementations fail not because the technology isn’t good enough, but instead because they don’t understand context. That word context is doing a lot of work here. While there are many forms it can take, […]
Empathy 101: Designing for Humans in the Age of AI
Augmented intelligence means building towards a future where AI can complement users’ abilities and help them grow in areas where they may need additional support.
Trust by Design: The Elements That Build Confidence
When decision-makers rely on large language models (LLMs) or other AI systems, they’re not just adopting a tool. They’re also accepting a degree of risk that comes from delegating judgement to a system they didn’t build and may not fully understand. Trusting the output of an LLM means having confidence that not only is it […]
Human + Technology Collaboration: Better Together
When people talk about AI or automation, it’s often framed as either-or: humans or machines. But the real power is in the and. Humans and machines working together, each doing what they do best, to create a system that’s smarter, faster, and more capable than either one alone. Why the Human Still Matters Tech can […]
From AI-Curious to AI-Serious: The Journey to Strategic Impact
When LLMs first entered the spotlight, many organizations rushed to experiment with chatbots and use copilots.
Then organizations shifted to apply AI in ways which promised measurable ROI, but for many the focus was on cutting costs, not driving growth. These projects often worked. They saved time, reduced costs, and impressed stakeholders. Still, something was missing…
In this article, we explore how organizations are shifting from AI experimentation to human-centered AI strategy.
The future isn’t just AI. It’s human+AI by design.
The Future of Decision-Making: AI, Trust, and Transparency
Trust is crucial for important decisions in life, business, and society. Trust in data. Trust in decision-makers. And trust in the procedures that govern critical decisions that impact lives. As society contemplates recreating human intelligence in rapidly advancing software, we will need to revisit aspects of how critical decisions are made in the first place. […]