Humans vs machines: Who’s winning? -I

Many robots vs human, humanity and technology. Pop art retro vector vintage illustrations. Image credit: Tech Talks  depositphotos.com

I was asked to write a short paper for Tech Talks on Humans vs Machines.  It has been published on August 30th and I’ll post it here with some comments as a corollary to the series of posts I wrote in the last month on transhumanism.

Enjoy!

The rise of the machines

Technology is providing new, more innovative ways to augment us – human beings – thus enabling us to better respond to a world moving at a faster pace, and more easily secure that all-important competitive edge for businesses and industry. Institutions and government are facing mounting social costs, while communities and individuals alike are looking for a healthier, happier life. These challenges and aspirations press researchers to push past technology’s boundaries to develop smarter machines, since these intelligent constructs represent the most practical way to augment our capabilities.

Since the beginning of Homo sapiens, we have crafted machines to help us; what we are seeing today is an acceleration of this process. Part of this hastening is the result of having reached a tipping point: we are no longer required to transfer human knowledge to a machine for it to become smarter. We have forged machines that can learn on their own by observing us, making sense out of big data, and watching experiences as they unfold on the web. Just as important is the ability of these clever creations to test their newfound knowledge both against other machines and internally through the use of virtual clones.

To be sure, Artificial Intelligence (AI) has progressed significantly, though it’s more in terms of its applicability than in terms of absolute theoretical progress. AI can do far more today because processing power is abundant, cheap and (almost) ubiquitous. This, along with pervasive communications, and sensors and storage capabilities, has led to an inflection point in the availability of data. The consequence is twofold: the data space is so big that it is beyond human comprehension, and it is fueling machines’ capabilities, intelligence, and continuous learning.

This process has just begun, and there’s no end in sight. Machines have evolved beyond their clockwork origins, and are likely to surpass humans in a growing number of areas.

Man over machine

Until now, building a better mousetrap has served to improve the human condition. We have consistently benefitted from machines and have always had the power to shut them off… and sometimes we did. Consider the devastating weapons that while immensely effective, could lead us down the path to wholesale destruction.

The growing issue is the vital role played by machines – both as single entities and collectively as infrastructures – means we basically no longer have the option of just “shutting them down”. Think about the power grid, with its hundreds of thousands of people working around the clock to ensure that it stays on. The idea of turning it off (e.g. for decreasing CO2) is simply no longer an option.

Surgery is becoming progressively robotized, and medical diagnostics have become fully machine-dependent. Automated machines today manufacture drugs. Pulling the plug on these operations would have dire consequences for millions of people worldwide.

Yet, we can still claim that we are using machines as extension of ourselves, leveraging them as stronger, faster, and cheaper hands. Because of this, humans still triumph over the machine, but it is up to us to decide where we go from here.

More recently, machines have risen to become more than merely our augmented hands; they are now beginning to amplify our cognitive capabilities. It’s subtle, but it is happening.

Most of us have a symbiotic relationship with our smartphone. But how often do you really use it to call other people? More often than not, we’re using our devices to call machines. Need help reaching a destination? Let your smartphone show you the way. Want to impress your guests by cooking a gourmet dinner? Get out your smartphone and look for a recipe. Feeling awkward? Dr. Smartphone can check your pulse, face color, and other health cues, and then offer advice.

These are but a few examples of how we’re starting to engage with machines, but the list is growing rapidly. In the coming years, we can expect more people to have a digital doppelgänger flanking them. On one hand, this twin will be a digital mirror allowing for monitoring of any telltale signs of health problems. On the other hand, it will take on a life of its own in cyberspace, becoming a repository of our existence, a sort of black box that can be queried at will. It could even become a means of simulating next steps, whether in business, education, health, or even entertainment, allowing us to determine the best path forward.

Comments:

  1. we are still the designers of our machines. If we were to stop today the evolution, current machines would not be able to take up and foster evolution by themselves
  2. the progress of artificial intelligence is making machine “potentially” able to learn independently of us. This learning is still limited to very specific areas hence these machines can progress only in their specific areas.
  3. Even in the very limited areas where today machines can learn and get better they still need humans once they break down and in general they all depend on “logistics” (like power) that is provided by humans.

Continues ….

About Roberto Saracco

Roberto Saracco fell in love with technology and its implications long time ago. His background is in math and computer science. Until April 2017 he led the EIT Digital Italian Node and then was head of the Industrial Doctoral School of EIT Digital up to September 2018. Previously, up to December 2011 he was the Director of the Telecom Italia Future Centre in Venice, looking at the interplay of technology evolution, economics and society. At the turn of the century he led a World Bank-Infodev project to stimulate entrepreneurship in Latin America. He is a senior member of IEEE where he leads the New Initiative Committee and co-chairs the Digital Reality Initiative. He is a member of the IEEE in 2050 Ad Hoc Committee. He teaches a Master course on Technology Forecasting and Market impact at the University of Trento. He has published over 100 papers in journals and magazines and 14 books.