What developments in AI are needed for us to reap the true advantages it can bring and is the world ready for it?
AI is a general term that implies the use of a computer to model and/or replicate intelligent behavior. Research in AI focuses on the development and analysis of algorithms that learn and perform intelligent behavior with minimal human intervention. Like most new technology, AI has become part of everyday life without us knowing it, whether that’s the spellchecker on your phone or the software sitting behind credit score calculations.
The global technology powerhouses have declared AI will change the way we live and work over the next decade but will the overall impact be positive or negative?
Habito, a UK start-up, is changing the way we find the best mortgage to suit our needs. A digital AI powered mortgage advisor walks you through your life events, attitude to risk and every other factor to identify the most appropriate mortgage. The software then scans all the mortgages available, over 15,000 in the UK currently, before identifying the most suitable for your needs. The whole process takes 20 minutes.
The key factor for the customer is whether the benefits of taking a purely algorithmic approach outweighs the personal reassurance a trusted human mortgage adviser may bring. At the same time, the trusted mortgage adviser might lean towards certain mortgage products he has used successfully in the past, personal preferences and hopefully in very few cases on the best commission rates they receive.
What is interesting is how few Habito customers take up the option to speak with a mortgage adviser when offered the opportunity to do so.
The same can be said of customers of Babylon Health’s virtual triage check-up over your smartphone. NHS has been offering this service to a million residents in North and Central London and Babylon Health now handles 15% of all triage consultations in the capital. For every 1,000 people 800 using the AI triage receive the results and go no further, 120 ask a doctor a question and 80 have a physical consultation. Even though the subscribers have unlimited access to doctors, the vast majority do not take up this option.
For any technology ease of use is vital, customers have to be walked through the process so the smooth automated journey becomes preferable to a less efficient existing telephone or face to face service. Brand recognition is key for any AI powered automated service and this only comes through user feedback. So new companies have to attract users to become a trusted brand, convenience is the main driver for more initial users, reassurance on safety of information and quality of service are essential to build a larger user base.
Where will this lead?
The Reform think-tank predicted that robots using AI could take the jobs of 250,000 public sector workers in 15 years. This may lead to a crisis not only in loss of income but also in self-worth for those adversely affected. Equally it could mean a change in roles so the robots take on the more onerous roles, freeing employee time for more valuable work. This could lead companies to develop more flexible work forces, bringing in talent as and when needed to complement a core team. It could also lead to a retraining of employees, developing skills around the current AI capabilities that can increase the benefits businesses gain from AI.
One common argument against the adoption of AI is the lack of ethics from a purely rational decision making process. The classic conundrum is around driverless cars, if presented with a situation where the car is about to hit a mother and baby but would hit an old person if it swerved, what would the AI decide? Personally, I think that very few individuals would react in a cold, rational manner faced with same situation and generally would try to avoid both even though this is a highly unlikely outcome. If AI is programmed the same in such adverse situations, would this be preferable knowing that the car reacted in the same way as a person or would the public prefer that the driverless vehicle reacts on a algorithmic, probability basis so there is a collative benefit over time rather than looking at individual instances. I guess that will only work if our human responses to life’s vagaries are rational rather than emotional, ie people become more like robots. Then we really are faced with “a march of the robots” as robotic evolution will ultimately turn us into cyborgs — humans integrated with machines.
In order to prevent such an outcome, the University of California, Berkeley in 2016 launched a centre to focus on building people-pleasing AIs. The centre is lead by computer science professor, Stuart Russell who in 2015 penned an open letter calling for researchers to look beyond the goal of simply making AI more capable and powerful to think about maximizing its social benefit. The letter has been signed by more than 8,000 scientists and entrepreneurs including physicist Stephen Hawking, entrepreneur Elon Musk and Apple co-founder Steve Wozniak.
The letter reads “The potential benefits [of AI research] are huge, since everything that civilization has to offer is a product of human intelligence; we cannot predict what we might achieve when this intelligence is magnified by the tools AI may provide, but the eradication of disease and poverty are not unfathomable,”
“Because of the great potential of AI, it is important to research how to reap its benefits while avoiding potential pitfalls.”
It’s precisely this thinking that underpins the new centre.
The problem isn’t consciousness, but competence. You make machines that are incredibly competent at achieving objectives and they will cause accidents in trying to achieve those objectives.”
To address this, Russell and his colleagues instead of trying to give the machine a long list of rules to follow, plan for the machine to be told that its main objective is to do what the human wants them to do.
“The intuitive mind is a sacred gift and the rational mind a faithful servant” Albert Einstein.
It sounds simple, but it’s not how engineers have been building systems for the past 50 years.
If AI systems can be designed to learn from humans they can start to build up an understanding of human values. The problem is we are all different and have different opinions and values.
So the goal is to develop AI that is a recreation of the human thought process — a man-made machine with our intellectual abilities. This would include the ability to learn just about anything, the ability to reason, the ability to use language and the ability to formulate original ideas. Roboticists are currently nowhere near achieving this level of artificial intelligence.
We do know that the brain contains billions and billions of neurons, and that we think and learn by establishing electrical connections between different neurons. But even neurosurgeons don’t know exactly how all of these connections add up to higher reasoning, or even low-level operations. The complex circuitry seems incomprehensible. Obviously, we need a better understanding of our own thought process before it can be replicated through AI.
Because of this, AI research is largely theoretical. Scientists hypothesize on how and why we learn and think, and they experiment with their ideas using robots.
It is generally accepted that robots will play a larger role in our daily lives in the future. The more widely they are used, the faster their capabilities will be developed. In the coming decades, robots will gradually move out of the industrial and scientific worlds and into daily life, in the same way that computers spread to the home in the 1980s.
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