For the longest time, my wife and I couldn't agree on cars or cameras. When it came to cameras, she would long for the manual SLR models. Having studied design and photography, and spent the hours honing the skill, shooting great photographs on film, and developing them in dark rooms, she had the expertise that Digital SLR seemed to ignore. I loved digital cameras, because it made taking good photographs easy. When it came to cars, I preferred manual transmissions, because it felt like I really controlled the car, having learnt to drive on manual cars. My wife much prefers automatic because it makes driving easier for her. Over the years both of us have made peace with these choices. But this reveals to us the fundamental truth about all tech: much of technology innovation tends to democratise expertise.
"In the future, everybody will be famous for 15 minutes" - Andy Warhol
Pattern 1: Much of technology innovation tends to democratise expertise.
This is historically true of so many things. From bridges that allowed everybody to cross rivers, without the expertise of boatmen, to matchboxes, that allowed us to start fires without the specialised skill of rubbing flint stones. The earliest cameras democratised portraiture. Kitchen gadgets democratise cooking related skills. And so on. Even the most current technologies of today are doing just that. AI is threatening to democratise much of today's white collar expertise - from traders and lawyers to claims adjustors and doctors. Satellite imaging is democratising the expertise of spies. One of my most favourite examples of this is 'the Knowledge' which is a course instituted in 1865, and valid till today, that typically takes 3-4 years to learn for any aspiring London Black Cab driver, and involves memorising thousands of landmarks and streets in the city. For decades, this has been the core to the value of black cabs. Today, smartphones, SatNavs, and Google / Apple maps have made this accessible to almost everybody. And as you read this, remember that products like Word and Grammarly are democratising the skills of spelling and grammar which most professionals today have spent much time learning and sharpening in school. Headline checking tools offer to give everybody access to editorial skills once highly sought after in the newspaper industry. Even fame has become accessible to everybody on the internet apparently.
"Don't mistake your Google search for my medical degree" - a million doctors across the world.
Anti-Pattern 2: Experts often resist new technology. This is not just Luddism.
So far so good, but here's the problem. We have a conflict of interest. Imagine that you've just learnt heard that there's technology that can do something amazing in the field of medicine - and be better than doctors. How are you going to figure out whether it's any good? The chances are, you'll ask somebody with medical knowledge - aka a doctor. Now ask any doctor whether they think technology can do their job. Don't be surprised if you're met with invective. The last thing any professional wants to accept is that a piece of software or a machine can do her or his job better. Part ego, part threat, the resistance is usually visceral. When the luddites attacked the mechanised looms in 1779, they were not yobs who were against progress, but instead, skilled and smart men who were taking action against machines they recognised were going to cost them their jobs. Even when jobs aren't threatened, the ego is. Most of us believe that we bring a unique set of intellectual tools and experiences to our jobs. And the reality is that technologies such as AI are still very rudimentary. For example, the world's most sophisticated language generator (GPT 3) uses 175 billion parameters, while the human brain has about a hundred trillion. The problem we've got is that it's taken AI 70 years to get to this point and it's taken humans a hundred thousand years. So right now, it's likely that AI tools are poor imitations of human capabilities. But with every passing day and year, the gap is shrinking.
Even at this pre-pubescent stage, technology has 2 big advantages over humans - it can be distributed, and it can specialise. We humans learn largely from our own experiences. But autonomous robots (or cars) can learn collectively. Every lesson can be learnt by all robots connected to a common 'brain'. And a technology product or tool can dedicate itself to a task exclusively, and process a million times as many data points for that task as a human can. The reason why computers are now better than humans at chess is because they play millions of games against themselves and keep getting better. A grandmaster by comparison can only play thousands of games.
Despite all of this (or maybe because of it), at every stage, it's the experts who will resist the democratisation because of the combination of hubris and threat. So listen to experts, but perhaps not about their long term superiority over technology.
And about that Google search on your strange symptoms before you go to your GP - it's likely that most of the time, the doctor will know better than you about how to interpret your symptoms. But for some small number of cases, when you have a specific and rare problem, it's likely that it'll be new to the doctor too. A smart Google search which connects you to others with the same problem or to opinions of experts who may have worked on that condition may actually give you a head start. It's likely that without a medical degree, you may still not know what to do with the information, or to understand the terminology or the risks. But it suddenly becomes a scenario where your inputs count as well as the doctor's knowledge. And nobody likes power shifts when it goes against them. Doctors, educationists, and automobile garages - they all resist the erosion of their accumulated expertise.
What business are you really in? - Theodore Levitt
Pattern 3: New technology builds new expertise
There is no absolute start and end point for technology and innovation. Technologies morph and blend into each other. And even as old expertise is democratised, the evolution and growing feature complexity of new technologies builds new expertise until that too is nullified by future technology. Keep in mind that cameras democratised portraiture before building a whole new area of expertise as camera tech got more sophisticated and complex. As digital cameras found their way into phones and digital photography skyrocketed in volumes, new expertise was immediately built phone based photography - lending itself to creating the best selfies or digital editing techniques. Filters came along and made editing photographs easier. And so it goes. Even as we quibble about whether AI can do the work of a paralegal, the creation of AI and its training, algorithmic modelling, and data management are all evolving areas of expertise.
So what does this mean?
What does it mean?
(1) whenever there is expertise that has created an economic advantage, there is economic incentive for technology that can make those skills accessible to everybody. A very basic example can be found in retail. A generation ago, when you went to buy anything from a TV set to a pair of shoes, you largely depended on the person at the store to guide you. The retailer had the economic power - they could nudge you in their chosen direction. Today, 99 times out of hundred, you will have done your homework on any significant purchase - size, colours, material, sourcing, technology, user feedback, energy consumption, comparative models, and much more. And the person behind the counter is likely to be reasonably new and will have a passing knowledge on all the products, rather than your level of depth on your particular chosen product. The seller is no longer the expert.
(2) often, a new technology will be dismissed by experts in a field because they are the ones intellectually or commercially threatened by the tech - so asking the experts may not give you an objective view of the technology, and especially not of its future trajectory. This is particularly harmful in organisations where leaders and senior technicians have the loudest voices. Not only will the corporation often ignore the emerging technology, but its best brains will actively argue against it - this is a double whammy, because it may well put your customers off. Smart companies work to give the proponents of new technology (aka the ‘new experts’) a voice and platform.
(3) any new technology will create its own impermanent expertise base, so businesses should focus on being able to shift expertise with new waves of technology. If Kodak had seen itself as a company focused on helping people create images of their lives, then they could focused on shifting to the new expertise. This is neither easy, nor is it a permanent as we've seen, so it might sound glib to say this in retrospect. Nonetheless, it's the only way forward for professionals and companies. Keeping in mind the time it takes to build organisational competence, this might require multiple bets and early investment, in the worst case, for nothing else but option value. And in the best case, to pivot into entirely new markets. Like the impressionists in the 19th century, when faced with camera technology.
Reading This Week
Augmented Humans - Brain Implants for Blindness: Helping blind people regain sight might bypass the eyes and use miniature video cameras and brain implants, based on this successful early example of the procedure. (Science Daily)
Dogs of War: It was only a matter of time before somebody (in this case, Ghost Robotics) put a machine gun on a robot dog. (The Verge)
Design: The need for making medical devices as sexy as Apple products.(Fast Company)
Mis-information: Facebook’s India problem. In short, a much more acute case of spreading misinformation. (NYT)
Future of Intelligence/ AI: Why Geoffrey Hinton, a pioneer of Deep Learning believes that in the future, Deep Learning will be able to do everything. We just need the scale. (MIT Tech Review)
Mobility: Electric Planes before cars? Why batteries might get wings soon. (Morning Brew)
Sustainability: We’re losing the climate race. The UN predicts a 2.7 degree rise in temperatures by 2100 at the current rates. That would be catastrophic. (Bloomberg)
Interesting: The secret life of fungi. And why we should all be mycophiles.