The Impact Of Artificial Intelligence Over The Next Half Decade
Why half decade? For those who may find awkward the reference to “half a decade” and not the “next decade” here is why: Artificial Intelligence (AI) is evolving at such a staggering rate that it is simply not possible to foresee what it will represent in 10 years’ time.
As Maurice Conti (Chief Innovation Officer at Telefónica Alpha and former director at Autodesk) reminded us in his TEDx talk in February 2017, that in the human history the “Hunter-Gatherer” age lasted for several million years, then the agricultural age lasted several thousand years, the industrial age has been around for a couple of centuries now, the information age has merely a few decades, and the AI age (although the concept was drawn in the 1950s) has in fact effectively started less than half a decade ago.
What Is Artificial Intelligence?
It is very easy to mistake AI for RPA (Robotic Process Automation), so let’s start by defining what sets them apart.
RPA results from developing detail instructions that are translated into code which a computer interprets while actuating a robot. Therefore, RPA enables the integration with mechatronics (robotic physical machines) to partially or fully automate human activities which are manual, repetitive and rule-based.
AI does not aim at accomplishing repetitive tasks based on a given set of rules. It aims at learning new ways of acting from either having performed or watched repetitive tasks. In essence, having the ability to make subjective decisions with the goals of improving the initially established process.
AI means moving away from programming and stepping into “Machine Learning”, where an AI is trained to “acknowledge” certain patterns, hence making its own decisions on how to proceed.
Nevertheless, once you enable AI to create code which will instruct RPA you have reached Cybernetics and created an A2IM (Autonomous Artificial Intelligence Mechatronics), such as some military drones (we’ll come back to later).
Some Facts About AI
To draw a picture of why I am being so assertive on my conviction let’s look at the following facts (not theory):
An experiment was initially performed in 2011 where both humans and AI were “asked” to identify what was shown in a blurred image. Human error rated at 5% while AI’s rated at 26%. In 2013, the experiment was repeated and the AI error rate dropped to 3%.
In 2015 an AI managed to almost beat the top poker players in the U.S. (and poker is a strategic “thinking” game where not merely the cards “have a role to play”). The main point was that the AI learned how to “bluff”- yes, really!
Also in 2015, an AI was able to accurately draw a picture which mirrored what was written in a given text.
Still, in 2015, Professor Pieter Abbeel and his team at UC Berkley AI Laboratory were for the first time able to “teach” a robot to “think for itself”. PR2 (the robot’s name) was able to successfully deal with pieces of clothing (something that does present itself twice in the same shape or form).
In 2016 and 2017, some AI challenges have produced unbelievable results:
Analyzing a still picture (from a video clip) and producing a short video (5 seconds) showing what would happen in a sequence of what the image shows. The AI could predict things such as someone falling to the ground or someone opening a bottle and drinking it or a dog running into the water at a beach, amongst other with 96% accuracy towards what really happened next.
Another experiment “asked” an AI to predict how a human would behave when faced with an unprecedented situation, after having analyzed videos of that same human behaving in other contexts. Again, a 92% accuracy rate was achieved. Have you watched “The Minority Report”? Yes, I know…
In January 2017, the AlphaGO AI managed to beat the best GO player in the world. OK. Why is it so relevant? Go is the most difficult game humans have managed to come up with; it has more permutations in terms of possible moves than the sum of all the atoms that have been calculated to exist in the universe!
A clear example of exponential AI evolution (although rudimentary and limited to one single purpose) is now starting to populate our daily life in the form of self-driving cars. In 2013, Google was struggling along with BMW (and others, although in secrecy) to make it work and today both, along with Tesla, have achieved to install an almost error-free self-driving AI in their vehicles upon client’s request – and other manufacturers are soon to follow.
Just out of curiosity, all these experiments had humans performing the exact same task and those managed an average accuracy of just 82%.
Remember the scene from “2001: A Space Odyssey” where HAL (the AI) politely replies to Dave it cannot open a door, clearly demonstrating “free will”? Well, rest assured that won’t happen tomorrow – although it won’t take a decade either.
It’s a silent revolution which is happening just as we speak and one thing we may be certain of a self-aware/self-teaching AI will be the last thing that humans will invent. Not because our kind will be wiped out by it, but because from that point onwards the creation of new technology will be done by the AI.
AI That You Can Use Today
Today, there are in fact several AIs which have been developed by companies and can be used by your company, here are some examples and the edge they represent:
Airbus has developed an AI that, given the specs of a new aircraft such as cabin volumetry, shape, target weight, fixation points, air flux requirements, temperature requirements, among others, is able to create the most efficient airframe for a cabin partition or a new type of seat (that is both lighter and safer than existing ones).
A Boston company called “Gamalon” has released an AI that can rewrite its own code based on “learned” probabilities instead of hard variables. This alone has the power of making the tedious part of AI development fully automated for IT companies to extend their portfolio towards AI offers.
AUTODESK, the Product Lifecycle Management solutions giant, have recently finished a solution called Bishop which is a precision drilling robotic arm attached to an AI “brain”. The human operator can tell Bishop that a given component needs a certain number of holes drilled for fixation purposes and Bishop will analyze the structure, what needs to be attached to that component and “decide” on where to drill the holes so that both structures are not compromised. Additionally, if it finds that the outcome will compromise any of the structures it informs humans about it and proposes alternatives.
An AI in the health sector analyses CT Scans and performs both the diagnosis (having proven to find in average 20% more potential health threats than a human) while proposing therapeutically procedures. With regards to the potential of cancer development potential, this AI can diagnose lung cancer with a 10% higher potential than human doctors.
If you cross-reference the information collected by a smartwatch (monitoring heartbeat and arterial pressure as well as body temperature) with a healthcare AI you can monitor chronical patients and mitigate potential life-threatening incidents, nowadays.
MarianaIQ is an “AI Rainmaker” (something that empowers sales), that goes about social media collecting information about personal interests and preferences, trends and “causes” of decision-makers at a given market vertical sector. Then, the information is analyzed and cross-referenced with both the client company as well as the target prospects’ profiles and personal networks. This bears the potential of enabling an accurate sales pitch to be forwarded towards either a decision-maker or a facilitator stakeholder.
AppZen is a back office automation tool that can go about a financial statement in detail (meaning the data in the ERP) and detect all the noncompliance and errors as well as where they have originated without failure. The company did a trial with one large corporate client where a team of humans did the audit simultaneously with the AI and the results showed the AI with 100% accuracy and the job done in 3 days whereas the human team took 1 and half months and the accuracy was at 86%.
Currently, there are AIs in use in several news agencies that correlate facts described in several texts (written or spoken) and merge them according to the established language, timeline and writing rules into one single news briefing text.
AI has also developed “Amy”, a virtual assistant that manages your schedule. How many meeting requests do you get in a week? How much time does it take you to deal with the back and forward messaging to arrange a mutually convenient time slot? Well, Amy takes care of it. Amy will “look” at your existing appointments plus personal preferences or constraints and exchange emails (as a human assistant) with your guest to find the most appropriate time and location for the meeting to take place.
The Real Danger Of AI
Many voices have risen over recent years to warn about the danger of not taking due caution towards the way AI is developed.
Professor Stuart Russel, the head of UC Berkley AI Laboratory, has testified before the UN back in 2015 about the real danger of “autonomous weapons” such as AI outfitted drones. Having a robot in service that can target and kill humans without the go-ahead of a person bears a colossal risk, remember “Robocop” or “The Terminator”.
Elon Musk refers the risks of Artificial Super Intelligence (as he names it) as being similar to dealing with nuclear weapons for it is much difficult to maintain the potential accumulated energy controlled than to release it.
Bill Gates takes on a straightforward approach bridging with the idea that as soon as the “algorithm” that allows humans to transform experiments into knowledge and deduction gets to AI, the overwhelming processing capacity of AI will immediately create an intelligence form that exponentially exceeds the human capability to even understand it. Now, the next step is to realize that a self-aware entity tends to primarily focus on its very existence and having a self-aware AI that realizes humans can terminate it, makes all the imaginable non-aggression to human’s rules that you may have initially imprinted, redundant.
Professor Stephen Hawking warns about the fact that a self-aware AI will immediately gain the ability of self-redesign/self-improvement at an exponentially increasing rate, which means its intentions, as well as basic components, will immediately be out of human comprehension’s reach. Meaning that we as a species will be faced with a much more intelligent entity than we could become in thousands of years. And these entities are capable to drastically act upon both our physical and logical world, having self-conscience and free will while knowing that we bear the potential of destroying it.
Ray Kurzweil states that AI will reach the human intelligence grade in less than 15 years and within 25 years AI will have exceeded human intelligence as well as intellectual capacity.
AI has been doubling in power on a yearly basis since 2010 and the trend has now moved towards exponential growth, so these predictions are off the chart, seem to be so by default rather than excess.
What Is Soon To Come
Here are some logical next steps in the realm of AI:
- Exponential growth in kind as in quantity of AI Cloud-based services offering the likes of the ones mentioned above under the what “you can use today” section.
- AI pets – Robotics and AI have evolved to a state that allows mimicking pet behavior even with regards to what is perceived as “intelligence”. So, the creation of pet-like robots which bear the potential of interacting with humans while creating an emotional bond is a definite possibility.
- Creative Writing – Although still complicated, it is one of the logical next steps for AI, soon to be found in a Cloud near you.
- Outsourcing to AI – Some of the examples herein mentioned are already available. AI offerings are based on public Cloud IT landscapes, therefore it is already possible for companies to outsource financial analytics or task a virtual assistant.
At the current trend, by 2020, a computer CPU will cost less than a Cent, therefore we will find them literally everywhere interacting with Cloud-based services and existing AI by consequence; this means AI (as evolved as they may be) will be literally everywhere (like, currently, electricity is).
Your personal assistant will be intelligent, so once you enter your house your AI-based personal assistant will check your mood via the bio info collected through the sensors on your smartwatch and set the light, music, TV shows, food and so on according to both your preferences and mood. And this won’t take a decade to happen either!
You will be able to play an all set of new virtual games where the game (meaning AI) will create the game scenarios and situations as a response to your actions or aspirations, either making it harder or easier to prevail as you wish.
You will get a fully automated health checkup every time you take a bath or use the toilet at your house. Body fluids and temperature will be analyzed by sensors and the data will be forwarded to an “AI doctor” that will be able to inform you if there is something wrong with you and how to proceed. Ok, maybe this one will take a little longer than a decade.
“ASIMO” alike droids will begin to be sold as “physical personal assistants” – and they’re not so much different from what you can see as the “common” robots in the movie AI; mainly to perfume nursing support to hold population.
Cognitive Augmentation – As Maurice Conti explained, we are already “augmented”. Each and every one of us have a smartphone which is connected to the Internet and can easily reach out to a simple service like Google to get immediate knowledge about some unknown fact of life upon needing it. If someone is in the middle of a public square and gets stung by a bee, he/she can immediately google what to do and which worrisome symptoms to look for. Soon, AI that can “foresee” our needs and provide best-fit alternatives towards them will be available.
As recently as July 2017, the news spread over the internet and traditional media about a Facebook AI that was shut down after having started to create its own language – so, this is already happening. Facebook was attempting to create an AI that could negotiate with humans, almost like an upgraded version of the above-mentioned. Having reached a successful version in terms of fluent interaction, they decided to go one step further by replicating it (another AI) and put them speaking to each other. The AIs started to interact and quickly moved towards developing their own wording abbreviations in a manner that is interesting for it mimics the way humans develop speech patterns.
The interesting part is that the AI failed to accomplish the prime objective which was to improve its ability to speak and interact with humans. However, it failed because it started to develop a way to better interact with another AI – and this is a point for some concern.
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This article was originally published on Tenfold.
Photo Credit: uwnews via Visual hunt / CC BY