The Second Arms Race: Artificial Intelligence
posted originally at naiss.io/blog
The second arms race is actually the third. The first one was the naval race during World War I, followed by the Cold War between United States and the Soviet Union, scaling up nuclear weaponry right after the end of World War II.
The human race has been able to manage the prisoner’s dilemma inherent to these competitions so far, and now faces a new test with the advent of a new technology breakthrough: Artificial Intelligence.
This is a series of articles on the topic providing a vision toward an artificial intelligence explosion in the context of current economic changes supporting a shift in our economy toward an altruistic model.
Introduction:
· Technological singularity seems plausible and recent advancements in machine learning and AI suggest the ‘intelligent explosion’ event is within reach in this century.
· An arms race of narrow AI entities will happen in the framework of today’s traditional economy. Strong intelligence or AGI will eventually emerge followed by an explosion of intelligence.
· New globalization processes driven by technology are fueling the sharing economy, as well as the 4th sector where public, non-profit, social and mission oriented enterprises are converging.
· The 4th sector is poised to grow and thrive enabled by the sharing and collaborative economy; mission driven enterprises will have more resources enabling them to play a key role shaping the right path for AI evolution.
· The AI arms race will provide ‘good’ and ‘bad’ entities in the context of existing and new economy environments (traditional and altruistic economies)
· We, humans, as a species, can succeed managing the risks of a superintelligence event as we did in the past overcoming other technology threats (i.e nuclear).
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We have the capacity to anticipate the future with a certain degree of precision. Our prediction accuracy is lower as we increase the time horizon we aim at.
It’s pretty straight forward for us to predict short term events, those more likely to impact our survival chances; mechanical or physical, like anticipating when a car is going to cross at the juncture we are on, or, more long term and qualitative, anything related to replicating our gene pool, for instance the chances to date a specific person of the opposed sex.
However, when we look further ahead in time, and, because of our brainpower limitations and the effort required we struggle to foresee all potential possibilities and combinations.
Our brains, during evolution, developed a pattern-based approach to efficiently solve this problem. Identifying patterns allow us to see the big picture of a possible future, although we remain unable to predict the smaller details within (stacking up to conform to the pattern).
The Singularity, as defined by Ray Kurzweil, arguably the biggest ambassador of this concept in our times, is a period of time in future where technological advances will evolve so rapidly (exponentially) that humanity will not be able to keep up with them.
This definition needs to be broad because is a concept coined after careful analysis of the evolution of many technologies. It looks into historical data and speed of change rather than specific events themselves (although Singularity is mostly associated to the dawn of a super-intelligence entity capable of self-improvement).
We say can’t see the forest for the trees referring to short term events clouding our ability to see the big picture. The opposite is true for forward-looking statements.
With sufficient historical data we can develop patterns (and see the forest) but we will remain clueless about details (trees).
To state the analogy, let’s have a look at a practical example, a piece of technology we are all very familiar with, our phones.
Wireless phones (smartphones) have undoubtedly been the protagonists of the technology revolution in recent times.
The way smartphone technology has been adopted is well described by the diffusion of innovations theory (Everett Rogers — 1962), expressed graphically by an S curve (logistic function) or the widely popular bell curve (derivative of the S curve).
The process is well documented using available data from smartphone manufacturers (sales of devices over time) to the point we can track and predict with a certain degree of accuracy what the future will be for this particular technology.
The graph for US smartphone adoption, now above 70% penetration (Horace Dediu — Asymco), follows accurately the bell curve pattern to the point we can predict overall sales volumes in the years to come (this would be the forest in our analogy), but we are unable to predict which manufacturer will get the greater share in the same way we couldn’t predict Apple’s iPhone explosive growth since 2007 (those are the trees).
Thus, in a competitive and evolutionary environment as the current economy creates, with sufficient historical data, these well known patterns allow us to anticipate how technology breakthroughs will penetrate the markets and impact the population as a social group.
Details (trees) remain hidden though. We can’t predict which species (corporations) will be winners or losers; however, the scope and length of the ‘race’, market size and time span can be forecasted with fair accuracy.
The social aspects of technology adoption, with increasing mobile computing and ubiquitous Internet, are shrinking adoption cycles.
The number of new technology breakthroughs is also increasing over time. The intuitive idea of a singular future with unlimited wonders driven by technology makes more sense than ever.
This vision has fuelled Sci Fi literature and movies since the 50ies. The concept of Singularity, a future time where technology outwits human capabilities, may be now perceived as stating the obvious, a self-fulfilling prophecy.
The question is when.
But, not so fast…. First, let’s ‘take a selfie’ of the present and look at today’s status quo.
Next: An end to Moore’s Law (Mack 2011)
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