The session AI: Rise of the Machines at the Milken Institute Asia Summit saw an impressive panel assembled to share their insights into the impact and opportunities of AI on businesses. Foresight Factory’s Director of APAC, Michael Agnew joined Ben Goertzel Chief Scientist, Hanson Robotics and Chairman of OpenCog Foundation, Virginie Maisonneuve, CIO of Eastspring Investments, Robert Morris, VP at Global Laboratories, IBM Research and the moderator Ralph Simon, Chairman and CEO of Mobilium Global Group and Senior Advisor, Laurel Strategies. What did some of the most intelligent minds in the industry have to say about the future of AI and the timeline of impact on businesses and us as consumers?

 

The rise of the machines

The statement: “AI brings a lot of uncertainty” incites very little contention. It’s the very reason the panel exists – because companies do not want but need to know how to act and adapt to the rapid advancements of the various types of AI technology infiltrating everyday life.

Virginie Maisonneuve of Eastspring calls it ‘digital Darwinism’, where only the fittest will survive. But how did we even get here?

AI has boomed in popularity in recent years but has been nurtured since the 1960’s. Critically it has been the success of applying the technology that has resulted in the hype and continuous advancements that we see today. Ben Goertzel, creator of Sophia, the eerily lifelike robot that opened the panel, states that “AI is going to pervade everything”. In the late 90’s we saw IBM’s Deep Blue defeat a world champion in chess and then in 2011, Watson won against two reigning Jeopardy victors. If anything could make someone sit up in their seat, it’s a computer winning over $77,000 USD. And so the world took notice.

 

The different types of AI

When we talk about AI, terminology like ‘deep learning’, ‘neural’ and ‘sentient’ come with the territory. Here’s what the vocabulary actually means and what their capabilities are, from the experts that build humanoids and worked on IBM Watson themselves:

Neural AI describes an AI that serves particular functions for example, analysing data or operating driverless cars. However, Goertzel explained that there will be more developments in the realm of general AI. This is when an algorithm can take what they’ve learnt in one domain and apply it to another that they’ve never been exposed to before, for instance a self-driving car could learn to operate a truck using its previous experience, without the help of its developers. During the transition process between these two types of AI is when algorithms absorb ‘human values and understanding’, incorporating this into their behaviour.

As for humanoids, they predominantly serve as a user interface for an AI mind cloud and are not siloed off but have the ability to be sentient and fall under the category of ‘general’.

When it comes to deep learning or a deep neural network, this type of AI looks after a specific task that can be executed unsupervised. Robert Morris shared that C-level executives and corporate strategists usually opt for deep learning systems, but this could potentially limit the AI portfolio of a company. The risk is that “you can’t explain what it’s doing”, which could lead to complications and even hurt compliance practices.

 

Financial services

“AI has been democratised [and] in every industry people can start [a business] with a very small effort”. – Robert Morris

When it comes to automation in financial services, we already see this being adopted by banks like DBS who have pledged to invest $20 million in training a digital workforce, which includes hackathons, e-learning courses, grants and scholarships. Furthermore, the Infocomm Media Development Authority of Singapore announced plans to boost adoption of AI and support fintech companies to expand globally.

When we asked consumers whether they were interested in a service which linked to their bank accounts and analysed spending to help them meet personal financial goals, the result was 48%. When we asked essentially the same question but used the term ‘artificial intelligence’, the response was startlingly similar at 46%. The conclusion we draw from this is that people are growing to understand the role of AI in our everyday and private lives.

Morris talks about the positive impact of AI in East Africa, where it has already been used to facilitate loans for those with no credit rating, based on digital breadcrumbs from smartphone data. The technology has meant that default rates and instances of fraud have been lower. AI can also be used by the government to share know-your-customer practices with local companies and smaller banks. By using blockchain (data management that enables AI to make it trustworthy and shareable) as well as AI analytics, valuable information can be dispersed securely, without revealing the data.

 

Healthcare

It’s quite clear that the rise of the machines is a response from us for faster, smarter and more convenient technology. Implications for this have become greater as the stakes are higher. For example, AI has the ability to make treatment decisions for people with cancer, supplementing the opinion of specialists.

This is where IBM’s Watson is most impressive – it can read 27 million publicly available medical journals that then tailors recommendations for doctors. And in spite of its ability for genomics, especially with chronic diseases like hypertension, depression and diabetes, Morris says that this “scratches the surface of healthcare”.

 

Watch the panel discuss AI and the implications for businesses

Is Asia the future for AI?

Already AI is implemented in Asia on a widescale. IBM in China have used AI alongside 4000 sensors and satellites, as part of the Internet of Things, to predict pollution levels from 3-10 days away. By understanding how it spreads, Morris says we can “reason with [its] sources” and then figure out how to stop pollution patterns, with minimum economic impact. 250 million people are directly affected by AI bettering the environment.

So is Asia the future for AI? The simple answer is yes.

Asia invests, whether its AI, fintech or natural resources. Furthermore, there’s a lot of runway for research and development – Asians make up 60% of the world’s population and have an unique phenome, yet less than 10% of medical literature apply to Asian subjects. Economic changes in the region have also resulted in the prevalence of chronic illnesses like diabetes in Singapore.

Foresight Factory data shows that Asian consumers are more interested in AI than anywhere else. 20% of this region’s internet users will own a smart home device by 2025, in particular intelligent home devices is an area for development and experimentation. We have already seen a large uptake with 1/3 of APAC consumers having used voice commands on smartphones, with the figures significantly higher in China and India with 45% usage.

 

If you plan for this, the future is bright.

 

“You need robotic eye implants” – Ben Goertzel

“The limits of what it means to be human is changing” – Michael Agnew

“Don’t let risk derail it” – Virginie Maisonneuve

“By themselves they won’t fulfil their potential, we have to work out how man can work out with machines” – Robert Morris

 

 

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