Andrew Ng (former Chief Scientist at Baidu, Co-founder of Coursera) is fond of referring to AI as the “new electricity”. Similar to how electrification ended up transforming every single industry during the 20th Century, AI is broadly expected to have similar (if not greater) impact in the coming years.
This post by Oscar Li does a great job encapsulating Andrew Ng’s thoughts as shared during a recent lecture at Stanford.
The social and business ramifications are easy to extrapolate / imagine: Anything that you can do now, you can do better with more AI and data. And as the technology that underpins AI continues to improve and the datasets continue to grow, AI will allow us (or machines) to do whole new things not possible before.
If you’re like me, it’s actually quite overwhelming to ponder the full implications of AI. But if AI is on track to transform the world like how electricity did, we should be able to learn some lessons and create some useful predictions by looking at what happened a century ago.
Lessons from Electrification:
- Everyone Electrified and then Electricity was no Longer a Differentiating Factor: Today, companies that use AI and data have an advantage over those that don’t. A similar dynamic existed a century ago. Retailers that were electrified had an advantage over those that didn’t. Factories that were electrified had an advantage over those that didn’t. Eventually all businesses either adopted electrification or were out-competed. However, once electrification was fully borne out, it was no longer an advantage. A similar dynamic also played out with air conditioning in the middle of the 20th century where early adopters had an advantage, but once every retailer adopted air conditioning, it became a necessity rather than an advantage.
- Electricity Changed How Business was Done But Had Less of an Impact on the “Jobs to be Done”: Electrification allowed businesses to extend their hours of operations, drastically increasing efficiency and productivity. Electrification also brought about new machinery and tools that similarly improved efficiency. In other words, electricity made businesses (and people) better at their craft but had less of an impact in terms of the goals that businesses pursued. Retailers remained retailers. Manufacturers remained manufacturers. Service providers remained service providers. This is perhaps the most interesting takeaway (or contrast) with current assumptions around AI – namely that AI will necessarily lead to “new” products / services.
- The New Business Model Created by Electrification was the Electric Utility: Although electrification had large ramifications on how existing industries operated, the only key new business model to emerge appears to be the electric utility to provide the fuel for the disruptive technology (I’m not quite sure if this statement is entirely accurate – if any readers have supporting evidence for / against, please do share). Similarly, how many new business models should we anticipate in the coming AI explosion? It’s clear that AI will be important for existing industries, but how many new types of businesses should we expect? Perhaps a “data utility”, but what else?
- Other than Utilities, No One Made Money on Electricity: Once every business adopted electricity, it was no longer a differentiating factor by and of itself. As a result, electrification become purely a cost of doing business. Only utilities made money off of electricity. Can this be extrapolated to AI and data? Will it purely become a cost of doing business?
- Electricity Led to a “Cambrian Explosion” in Hardware: Although electrification appeared to merely change how businesses were run, it did lead to many new hardware products such as light bulbs, phonographs, radios, televisions, etc. Turned out that the best way to monetize electricity other than operating a utility was to produce hardware. This was the genesis of General Electric. Perhaps that is also what we should expect of AI.
These are just a handful of lessons. There are probably more that can be added to this list.
Taking these into account, it’s not outrageous to ponder whether AI can truly be monetized if not offered as B2B service (e.g. the utility model) or bundled with hardware (e.g. Amazon Echo, Siri / Google Assistant / Cortana in devices). Are there alternate monetization pathways if neither of these are feasible?
One thing that is an interesting contrast between AI/data and electricity is that AI algorithms and datasets are not commodities like electricity. Every utility’s product is the same. But AI algorithms and datasets are not interchangeable. What are the implications of having non-interchangeable “fuel” for one of the most disruptive technologies of the 21st Century?