This is part 21 of “101 Ways AI Can Go Wrong” - a series exploring the interaction of AI and human endeavor through the lens of the Crossfactors framework.
View all posts in this series or explore the Crossfactors Framework
The financial markets are rocky as tariffs are introduced to on-shore manufacturing in the US. What does this mean for the hardware we’ll be buying in the coming years?
Physical reliability is factor #21 in my series of 101 Ways to Screw Things Up with AI.
But wait, what does the reliability of physical products have to do with AI? I’ll get to it!
What is it?
Physical reliability is the ability of hardware to function consistently and accurately over time, without failures or malfunctions while being resilient to its environment.
Why It Matters
Our interactions with digital systems are mediated by physical devices, like phones, laptops and TVs. But there is also a notable trend of traditionally analogue devices becoming “smart” and connected and having interfaces that go well beyond physical buttons. Just the other day, I saw a smartphone-connected toaster with a touchscreen!
This creates a complicated relationship between the physical goods we purchase and the evolving software they depend on. Companies know they need to strike a balance between creating a physical product that is durable to its intended use for a timespan that will not disappoint its customers. But they also know that they can’t let existing hardware hold back software innovations, whether this innovation is from them or the broader market.
Physical hardware has been outpaced by software in several areas. Connectivity (5G, wifi6), resolution (4K, 8K), media codecs (HDR, Dolby Atmos), digital rights management (Widevine), operating systems (both desktop and mobile), digital ecosystems (Nest, Hue, Matter). I propose that the pace of these innovations has had to fall in cadence with our expectations of the longevity of the hardware that would have to be replaced. TV panels dim or get dead pixels, phone screens crack and batteries fade.
But this cadence will be disrupted by AI if it is to fulfill its promise of accelerating innovation and provide new capabilities.
Real-World Example
Televisions are a great example of how the physical reliability of a product interplays with the innovation seen in a product’s marketplace. For a long time, televisions saw incremental changes in size and form factor that were backwards compatible. Innovation was left mostly to the peripherals with an array of connectivity options. It was not uncommon to see units that were over 20 years old being relegated to basement duty.
Two things happened. Televisions became smart and connected, and input costs were reduced as glass and cathode ray tubes were replaced by new panels. We’ve seen the hardware continuously evolve to keep up with connectivity, resolutions, online platforms, etc. At the same time, the average television only lasts 5 to 7 years before being replaced, with units failing in less than 5 years being common.
Key Dimensions
Planned obsolescence - no conspiracy here, simply a result of incentives.
Innovation cycle - hardware and software roadmaps must be (somewhat) in sync.
Sensors - their reliability is critical as they continue to increase in numbers.
Soft-bricking - when perfectly good hardware is rendered useless by software problems, or discontinued software services.
Take-away
Every piece of electronic waste has a story.