This week we are leaning into multiple metaphors: AI as a mirror, UX design as a window or room, and life as information. Plus: read about Michael Levin's upcoming presentation at the Imagining Summit, Helen's Book of the Week, and our upcoming events.
It’s easy to fall prey to the design illusion that because LLMs look sleek, they must be well-designed. But aesthetics alone do not equal design. As Steve Jobs once said, “Design is not just what it looks and feels like. Design is how it works.”
It’s curious that these two papers, tackling such similar ideas, came out at the same time. Is this coincidence, or does it tell us something about where the study of life and intelligence is heading?
We are dedicated to unraveling the profound impact of AI on our society, communities, workplaces, and personal lives. To truly grasp this transformation, our approach is rooted in engaging with core concepts such as critical thinking, logical analysis, and the scrutiny of underlying assumptions, principles that are essential in the realm of philosophical inquiry.
Now that more machine learning-based AI has been deployed in more places, human skills are being replaced in finer slices with new automation technologies. What has been observed in traditional blue collar work is that not all AI is good enough to increase the value of the output.
How AI could help our reasoning when it's most flawed: aka when we're subject to cognitive biases.
Resolving a fundamental incompatibility with AI in human decision-making
Most decisions and most deciders are hybrids. Some machine, some human. The trick is to imagine all the ways that humans figure out ways around, over, and through the machine when what they really want is to make the decision themselves even if it means sacrificing accuracy.
Everyone likes to follow their intuition because it’s the ultimate act of trusting oneself.
WFH surveillance is growing but employers need to move on.
The math of COVID-19 may mean some level of opt-in tracking is vital to stop repeated outbreaks
Humans think in terms of 1,2,3,4 lots and lots, while machines think in billions.
If Clearview is normalized, we're not who we think (or hope) we are.
Why we need to keep talking about Ring and "plug-in surveillance."
How should we think about this super-convenient yet dystopian tech?
What does it mean if AI is doing the job of government employees?
The Artificiality Weekend Briefing: About AI, Not Written by AI
