Intelligence Machines

By jasonz

I watched a TED Talk presentation by Kevin Kelly, an executive editor of the Wired magazine, on how AI can bring on a second Industrial Revolution. The presentation analyzes the various stages of human evolution and discusses how artificial intelligence would become the center of the next phase of our technological evolution.

In his presentation, Kevin Kelly points out computing devices are derived from physics and nature despite all the wonderful things that they have done for us in the recent years,. Modern computing devices operate on nothing more than wires and switches. Computer programs simply make recurring patterns based on sets of instructions given by humans. As a result, regardless of directions of technological development, technology has tendencies. Kelly compares tendencies of technology to the movement of raindrops, while the movement may be erratic, the general direction is downward. Similar to raindrops, the general direction of modern technologies can be predicted despite the complexities behind them.

Kelly points out artificial intelligence will be the major area of research and development in the next stage of our technology cycle. Research and development effort in this cycle will be focused on making computer programs smarter and more intelligent instead of just softwares that help us perform repetitive tasks. He coins this next stage of technology cycle “cognification”. To exemplify the idea of “cognification”, Kelly brought up Google’s AlphaGo, the computer program known famously for defeating the world’s Go champion. Kelly also brought up Deepmind, another Google’s computer program that is capable of learning how to play video game.

Kelly points out our idea of artificial intelligence is generally misguided. We tend to think of artificial intelligence as analogous to a single music note that has only one attribute: loudness. He sees artificial intelligence is a symphony of different music notes in which deductive reasoning, spatial reasoning, memories all have roles in defining intelligence. As we change arrangement of “notes”, artificial intelligence can help us in different ways. For example, GPS device is capable of pinpointing our location because we program it to be good at spatial reasoning. Search engine is good at finding information because we program it to be good at deductive reasoning. As technology evolves so does the need to create different arrangement of “notes” to meet our other computing needs.

The presentation concluded with an analysis of the stages of human evolution. Kelly predicts that we are at the verge of next stage of technological evolution in which artificial intelligence, like steam power in the Industrial Revolution, would change the way we live. Machines would take on new meanings. Computer programs would become more than just productivity applications. While artificial intelligence may set us up for a future in which many jobs would be replaced by machines, it cannot do it easily without the help of humans. The rise of artificial intelligence would also engender new jobs and opportunities. We can take advantage of these opportunities by learning, understanding and embracing artificial intelligence.

While I do agree with Kevin Kelly’s prediction that research and development effort will directed to creating smarter and more intelligent technology, I think the word “intelligence” can be overused these days in describing the future of machines. According to Wikipedia, “intelligence” can be defined “in many different ways including as one’s capacity for logic, understanding, self-awareness, learning, emotional knowledge, planning, creativity and problem solving. It can be more generally described as the ability to perceive information, and to retain it as knowledge to be applied towards adaptive behaviors within an environment or context” Kevin Kelly’s vision on artificial intelligence reminds me of Phoebe Senger’s article that tries to give machines cultural identities. In “Practices for a machine culture” Senger points out that “the hope is that rather than forcing humans to interface with machines, those machines may learn to interface with us, to present themselves in such a way that they do not drain us of our humanity, but instead themselves become humanized” While machines that are capable of learning and problem-solving are on the horizon, we still have a long way to go in bringing other aspects of intelligence such as emotional knowledge, self-aware, and creativity to “intelligent” machines using just wires and switches.

I agree with Kelly that our understanding of artificial intelligence is limited. We are often sold on the idea of “intelligent machine” but we don’t understand the tremendous amount of effort involved in creating it. Even with advances made in AI architecture in the recent decade (“Why Deep Learning Is Suddenly Changing Your Life”) and the progress in natural language recognition using computer softwares (“Introduction to Natural Language Processing”) I think there is a long way for artificial intelligence to revolutionize our lives. Considering frequency of the words “artificial intelligence” appear in science journals and technology web blogs, I have yet to see any noticeable way “intelligent” machines are impacting our lives. Given the vast amount of resources tech companies like Google and Apple have poured in AI research (“Google Opens New AI Lab And Invests $3.4M in Montreal-Based AI Research”) and considering the fact that bots in video games have been learning our moves and beating us again and again in boss fight for many years, Google’s AI learning how to play video game and AlphaGo defeating the world’s Go champion isn’t all that impressive. Again, as someone, who is not involved in AI research, I am most likely underestimating the effort involved.

As an avid follower of emerging technology and fan of science fictions, I am always looking forward to an Utopia in which robots can provide assistance and answer to our need in meaningful ways. For this reason, I recently purchased a Google Home device, a Google product that represents Google’s latest attempt in bringing artificial intelligence to our homes. While the product is marketed to be the portal to Google’s most advanced AI platform. There is very little it can do other than playing music at the command of your voice and giving you generic answers to general questions. If Google Home embodies our vision of future artificial intelligence, then there is a lot more work to be done. In conclusion, while I am more inclined to Kelly’s hopeful vision over techno pessimists’ view of artificial intelligence, I think we need to educate ourselves about complexities and technical challenge of artificial intelligence before judging its potential.

Sengers (2000), “Practices for a machine culture: a case study of integrating cultural theory and artificial intelligence”

Roger Parloff, “Why Deep Learning Is Suddenly Changing Your Life” Web, Sept 28, 2016

Matt Kiser, “Introduction to Natural Language Processing” Web, Aug 11, 2016

Darrell Etherington, “Google Opens New AI Lab And Invests $3.4M in Montreal-Based AI Research”, Nov 21, 2016

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By jasonz

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Co-evolution of Humanity and Technology

By jasonz

As much I enjoy reading Norman’s thoughts on the co-evolution of humanity and technology in his article from The Invisible Computer. I find his views on the technological impact on humanity to be a bit pessimistic. He sees technology and machines as some foreign entities that are beyond our control while overlooks many aspects of technology such as its potential as a tool for creation and knowledge transfer.

While Norman makes a good point suggesting people are” forgetful of details, with a poor sense of time, a poor memory for facts and figures, unable to keep attention on a topic for more than a short duration, reasoning by example rather than by logic, and drawing upon our admittedly deficient memories of prior experience.“ I think comparing humans to analog is a questionable analogy. Analog technology was created for the purpose of storing and reproducing information in a systematic way. It is as much machine as any modern technology, but dated. Calling ourselves analog is suggesting we are still living in the past. In Norman’s view, ”people are analog, insensitive to noise, insensitive to error. People extract meanings, and as long as the meanings are unchanged, the details of the signals do not matter. They are not noticed, they are not remembered” I find it hard to agree with this statement. While we do have high tolerance for errors, we are sensitive to noise, sensitive to error. Our accumulated knowledge and experience have taught us noise is detrimental to decision-making. We spend tremendous amount of time and effort to minimize errors through documenting, reproducing and examining data to identify patterns. With the help of technology, we are constantly learning from our mistakes and trying to make sense of world through analyzing new and historic information.

Norman points out that “human beings are the results of millions of years of evolution, where the guiding principle was survival of the species, not efficient, algorithmic computation.“ Norman would be right if we still live in prehistoric times as hunters and gatherers. When people started forming societies that were organized around agriculture and institutions, our priorities shifted. As population grow so does our need for stability and predictability. Our obsession with efficiency and predictability can be traced back to our need to make better forecast to increase food production in order to sustain an ever-growing population. Our obsession with stability is needed for governance and establishing orders. Human beings have “co-evolved with social interaction, cooperation and rivalry, and communication”. Society would not have thrived and progressed without stability and improved efficiency in tools making and resource utilization made possible through technological progress.

Norman points out that technological progress and our obsession of efficiency in production have reduced us to just machines in an assembly line “hence too came the dehumanization of the worker, for now the worker was essentially just another machine in the factory, analyzed like one, treated like one, and asked not to think on the job, for thinking slowed down the action.” While this is somewhat true, technological progress has the potential to save us from dehumanization by automating low skill jobs and give us more time to focus on creative tasks that require cognitive skills. Although there have been numerous debates on the economic implication of job displacement by technology, improved efficiency through automation have make goods and services more affordable and accessible. Advances in technology have also created many job opportunities for the creative industry and information professionals. Norman points out the issue that technology has moved so fast that we are unable to keep up. “The slow evolutionary pace of life is no longer up to the scale and pace of technological change. The accumulation of knowledge is enormous, for it increases with every passing year. Once upon a time, a few years of schooling — or even informal learning — was sufficient. Today, formal schooling is required, and the demands upon it continually increase.”  While I believe Norman’s statement resonates with many of us who are always in pursuit of new knowledge to stay competitive in the world. I feel that knowledge does not accumulate perpetually. Knowledge becomes obsolete as we find better ways of doing things. For example, while it is helpful to understand machine codes, not a lot of software engineers use machine codes for programming. New knowledge supersedes old knowledge. Whatever knowledge we find relevant today may not be relevant a decade later. Our pursuit of knowledge can go as far back as the prehistoric times when we sought ways to identify weather pattern and better farming techniques. Technological advances facilitate the transfer of information to help us stay informed of nascent and relevant knowledge. There is no shortage of vast libraries of digital information and self-guided online education. The sufficiency of education is subjective and highly dependent on individual need. It is up to our individual choices to decide whether to take advantage and adapt to the ever-changing world.

Norman brings up some interesting points but I find his views to be a bit dated. I do agree with the fact that technology needs to be created in a way that should complement us, but I find it questionable that “we are compliant, flexible, tolerant. Yet we people have constructed a world of machines that requires us to be rigid, fixed, intolerant.” Machines do not require us to be rigid and intolerant of errors. Machines are programmable and follow rules set by humans. Machines are as flexible as we build them to be. The way machines are built is a reflection of our capabilities in applying knowledge to build tools to advance our cause. With advances in digital technology, electronic devices have become portable and computer processors have become much more powerful. The costs of producing and storing information become much cheaper and access to information has become much easier. Without accuracy and precision, much of technological progress that we have come to appreciate would not have existed today. Although “digital signals are limited in values”, they have enabled much creativity and information freedom. As complex as computing devices have become, they are still largely single-purpose tools that cannot make decisions and only capable of performing tasks in repetition. Machines are tools that help us to create better tools. While I do agree with the fact that “We have constructed a world of machinery in which accuracy and precision matter. Time matters. Names, dates, facts, and figures matter. Accurate memory matters. Details matter.” I don’t think we have forgotten we are still good at experimenting and inventing through trials and errors.


Norman, D. A. (1998). The Invisible Computer: Why Good Products Can Fail, the Personal Computer is So Complex, and Information Appliances are the Solution. MIT Press. Chapter 7: Being Analog

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