We Trained Machines To Think Like Humans, Here’s What Happened Next
This article originally appeared on the Salesforce blog.
We can predict the future, to an extent. Science fiction writer Isaac Asimov, often cited by futurist Ray Kurzweil as an influential thought leader in the classic debate between man and machine, theorized that human behavior can be predicted in aggregate over a long period of time. So, if we believe that past behavior is a good predictor of future behavior, we can take a good guess at what the far future holds for us. Applying an anthropological lens to our relationship with machines, we have observed some definitive patterns in technology:
Yesterday’s Generation: No Automation
Today’s Generation: Automation
Next Generation: ?
If this pattern continues, then the next generation of technology will be autonomous. We’re already seeing this become a reality. Companies have launched self-driving cars and computer scientists have trained machines to autonomously complete video games.
Recently, Google shocked the world with its advanced artificial intelligence (AI) technology when its computer program “AlphaGo” scored a victory against grandmaster Lee Sedol in the game of Go. Researchers view the victory a significant milestone for AI, even more important than IBM’s “Deep Blue” victory against chess grandmaster Garry Kasparov in 1996. AlphaGo’s founders remark that their technology learns from experience in real time, using a new class of algorithms called convolution neural networks, computing millions of sequenced strategies in just a few seconds. As machine intelligence approaches conscious thought, what role will humans play in a world where smart machines can make our decisions for us, autonomously? Global thought leaders have endorsed a human-centric approach to AI, lest we risk losing our “humanness.”
As machine intelligence approaches conscious thought, what role will humans play in a world where smart machines can make our decisions for us, autonomously?
The autonomous world has several implications. Companies will see business functions blur. Today’s automation of business processes will collapse functional departments and people will have entirely new job responsibilities. As an example, companies have now automated the entire “quote-to-cash” business process, connecting the sequence of events that starts from a customer quote (sales department) and ends in revenue recognition (billing department). In the future, a single employee will be able to orchestrate that entire process and more.
Today’s automation of business processes will collapse functional departments and people will have entirely new job responsibilities.
A recent study predicts that more than 50 percent of occupations will no longer exist in 2025. A new generation of workers will emerge. They will live and work in the new autonomous world. Managers today are redrawing organizational charts with titles such as Data Scientist, Customer Success Manager, IoT Manager, Developer Evangelist, and Chief Digital Officer. These new classes of workers will be responsible for the “full stack,” threading and stitching various parts of business and technology layers. Advances in autonomous technology will abstract away all the complexities and inner workings and help us do more with less. Today, you don’t need to understand how a combustion engine works in order to drive a car. Tomorrow, you won’t even need to know how to drive.
Advances in autonomous technology will abstract away all the complexities and inner workings and help us do more with less.
What’s also interesting is that the rate of change is accelerating. As data increases exponentially, we’re arriving into the future faster. Winwood Reade once said that man in aggregate is a mathematical certainty. Given enough data, we can predict almost anything.
Entrepreneur and investor Peter Thiel often talks about the importance of finding secrets. The secret here, hidden in plain sight, is that data rules the world. With data, one can develop novel algorithms and train thousands of machines to be autonomous. Today, data resolution is increasing astronomically thanks to cheap “internet of things” sensors and storage capacity. Enterprises and upstarts alike are building better tools to consume that data, making algorithms much closer to approximating conscious thought.
The secret here, hidden in plain sight, is that data rules the world.
But pure data volume won’t do in today’s hyper competitive markets. You’ll need well-formed, groomed data collected over stretches of time in order to make accurate predictions. Thus, longitudinal data will be the currency of the future. Knowing the sequence of actions taken by millions of customers over time is a prerequisite to pattern recognition — and from there, prediction. Knowing what your customer will want next — and being able to act on that insight — is the future. Loan companies are already using an applicant’s digital history, not their credit score, to determine creditworthiness. So, your history of actions online can determine how you’ll behave in the future. Today’s marketers use “customer journey” algorithms to determine which sequence of emails and offers will work best with customers. In the autonomous world, we can’t even begin to imagine what machines will be able to achieve on their own.
If technology will allow us to achieve more than we could ever imagine, where does that leave humanity? How will humans continue to innovate in a world where machines do all the thinking and decision-making for us? In the quest to amass more data, we seem to have forgotten how we even got here in the first place.
In the quest to amass more data, we seem to have forgotten how we even got here in the first place.
Beyond farming and collecting data, we need to think about how we can add value to our customers, neighbors, and society. To the extent that we can predict the future, business leaders should be designing better human experiences into their products and services. After all, our customers and business partners are also human. Knowing that all technology will become commoditized just like any other “shiny new object” offers us a sobering perspective on the importance of the human experience. Thus, the most valuable contribution from business and civic leaders is human experience design. Human experience design is based around taking accountability for which values and principles should be imbued into technology. Our time should be spent deeply understanding technology’s implications for its users. Assuming responsibility for the design’s final outcome will help leaders find the best use of technology for humans.
Thus, the most valuable contribution from business and civic leaders is human experience design.
The leaders of tomorrow will compose sequences of sequences to design whole new perspectives from which to view the world — whether it is to help our children make smarter financial decisions as they grow older or empower employees to provide customers a better service experience throughout a customer’s life. They will need to be the architects and keepers of these next-generation, lifetime “customer journeys.”
For business leaders and entrepreneurs seeking not only to create value, but also to capture it, the creative constellation of these experiences will provide sustaining competitive advantage. Why? Because most will fail to storyboard the experience. We’ve relied on machines for so long that we’ve forgotten how to imagine. Someone — or some “thing” — has been telling us how to live, what to eat, how to decide. Designing experiences for customers will require a much deeper, human understanding of customer needs, challenges, and aspirations.
Creating better experiences for one another is not just what we should do but what we must do. Isaac Asimov’s second rule of robotics says that “A robot must obey orders given it by human beings except where said orders would conflict with the First Law.” We are ultimately the arbiters of technology — past, present, and future. As such, our leaders should build products and services to reflect how we wish to see the world.
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