Reflecting on the Impact of Digitization

Before the age when history was written down, it was woven into long and rich narratives, which were recounted with great care and thus served to perpetuate history itself. How does all of this interaction change in an era where it seems everything is recorded and stored? We take thousands of pictures, but can we find the one that strikes the emotion of the moment like the single dog-eared photo we saved from years gone by? How does our world change as more things become digital?  I discuss some of the risks and opportunities in the article Do Robots with Viruses Get Sick Days?  

The Fears of the Past: Computers will get smarter than people

In 2011, the reigning champion on the popular TV show Jeopardy was defeated by Watson, IBM’s cognitive super-computing superstar AI agent. Similar victories for machines were captured as Deep Blue beat the reigning chess champion in 1997, and last year when the Chinese game of Go (which some say is an order of magnitude more difficult than chess) was dominated by Google’s AlphaGo. In all of these cases, there were numerous articles written about how machines were finally “smarter” than people. 

More and more, it seems, machines will be required to explain themselves to be relevant to humans and for humans to trust.

Yet in “victory”, the machine in question was designed to do one specific thing extremely well. It defeated a human, with a human brain, but only at that one very specific task. It would be unreasonable to expect Watson to successfully interpret the emotional impact of an opera, which is uniquely personal, and often difficult for lovers of the form to explain their own reaction.


Another argument that still sways in the direction of humankind is that of evolution. The one thing that we humans seem to do well is usually get better at things. Most AI machine algorithms too have some method of improving, either by additional training from humans or by observation of many iterations of data. AlphaGo, for example, is particularly designed to learn from watching human behavior or playing against itself and learning from positions that emerge in those games. This type of learning, however, is still largely constrained to a particular problem or objective. That characteristic of machine learning changes somewhat with neuromorphic methods, designed to mimic the operation of the human brain, but even these methods are constrained to a very specific type of evolution that is very much pre-conceived.

In the past, our perception of digitization was largely based on improvement: doing things faster than people. With time, machine capability evolved to allow machines to do things that people could not do at all. Nevertheless, machine capability remains highly focused on a pre-determined capability or method of learning. Certain capabilities which rely on uniquely human emotion or versatility are still well outside the range of automation.

The Fears of the Day: Computers are changing humanity

Lately it seems there are digital devices everywhere. Technology astounds. Digital devices are making water cleaner, helping to educate children in remote regions, and augmenting health care assistance to otherwise marginalized individuals. It’s not all necessarily good. There are concerns about having too many “devices,” children not spending enough time with physical activities, the loss of intimacy in communication, and the erosion of privacy.

More and more, it seems, machines will be required to explain themselves to be relevant to humans and for humans to trust. In a recent Churchill Club paired luminaries session I did with Dr. Inderpal Bhandari, Global Chief Data Officer of IBM, he put the challenge very succinctly, stating “The bigger examples are actually going to be in the realm of human endeavor in terms of keeping up with the data, in terms of establishing context and using these agents in a way to augment that intelligence. I think that's where the explanatory aspect is going to become really critical. You know you can't have the agent without it being able to explain what it's presenting back to the person.”


We are living in a time where it is becoming increasingly important to understand not only what our digital agents are doing, but also how those agents may be changing the way we act and react. It is how we implement technology, and how we understand the actions of our electronic agents, that portends the impact on humankind.

The Fears of the Future: My boss is a robot

Like any emerging field, not everyone agrees on the best way forward. Recently, some of the greatest minds such as Dr. Stephen Hawking have warned that AI could actually effectuate an end to mankind if not properly managed. I take these warnings quite seriously, but I think there is hope.

My biggest concern is if we become complacent. I don’t worry about taking direction (to some extent) from a robot. I already take direction from automation. My phone alerts me to an upcoming meeting and I go. My fitness monitor tells me I’m not walking enough and I get up and walk. The danger, it seems to me, is in surrendering our will to a machine and allowing that surrender to be an excuse for rational thought. If my GPS tells me to turn the wrong way down a one-way street, I am not absolved from ignoring that direction because it defies rational behavior.

From digital malfeasance to the complacency that comes with expecting all difficult problems to be solved by machines, we clearly have evidence of a shift in our views and expectations of the machines in our lives. As AI continues to advance, as the Internet of Things continues to connect things that were otherwise isolated and out of sync, and as new advances in computing make strides never before imagined, we have work to do to make sure that we use the excess human capacity created to improve ourselves and the world we live in.

Digitization is neither good nor bad. It is. The degree to which it will have a positive or negative impact on society and the world are entirely up to the creators of new technology and the consumers of that capability.

The challenge, as I see it, is to embrace the digital evolution going on around us, but to be thoughtful about how that digitization may be exacerbating marginalization, driving out creativity, or otherwise bringing about unintended consequence. There is still ample opportunity to serve the underserved, to think new thoughts, and to innovate in ways that far exceed machine capacity. The choice is entirely ours.

This article was originally published on LinkedIn.