Page 20 - EngineerIt August 2021

ICT ARTIFICIAL INTELLIGENCE

Darwinian evolution, including survival
of the fittest, to build AI programs that
improve generation after generation
without human input. The program
The great AI matter of days, and its designers think
replicated decades of AI research in a

that one day, it could discover new
approaches to AI.
“However, this is still all theoretical.
Bearing in mind that these organisations
smokescreen have access to most of the world’s
consumer data and billions of dollars to
keep pumping into research, we have
to ask if AI is practical for the average
organisation right now. With everything
being experimental, what value can a
company gain from trying to jump on the
AI bandwagon?”
If and when the public, governments and the investment Firth adds that it’s also very difficult
community recognise that they have been sold an unrealistic to see the value offered by AI in data-
picture of AI’s strengths and weaknesses that doesn’t match sensitive industries. “In banking, for
reality, a new AI winter may commence. example, it is already challenging to ensure
regulatory requirements are met. Financial
services institutions already have to look
hile it seems like every second conversation over the past year has been about carefully at what data can and can’t be
technology enabling remote working, this has not slowed companies’ interest – moved across borders, and if AI engines
Wand investment – into tech like the Internet of Things (IoT), Machine Learning requiring even more data come into play,
(ML) and Artificial Intelligence (AI). Unfortunately, too many businesses are not realising the I don’t see how these types of industries
value from these investments, says Richard Firth, CEO of MIP Holdings. can make use of them unless the AI
“This is partly because these emerging technologies are part of a long-term strategy engines are in-country or on-premise”.
and are only expected to start impacting on the financials further down the line, and With embedded AI still being far from
partly because a lot more work needs to happen before they can start delivering on their reality, and with investments into the
promises. AI is a perfect example. In the rush to AI, many companies have neglected to put technology still far from paying off, Firth
the right foundation in place,” he points out. says that advances in AI are unlikely to
“The phrase artificial intelligence actually offers a false promise. The term misleads be nearly as disruptive—for companies, for
decision makers into investing in advanced analytics before their organisation has workers, or for the economy as a whole—
reached sufficient data maturity. You simply can’t have AI unless you have data, and the as many observers have been arguing, for
right analytics in place, because the AI feeds off the data that informs its decisions.” a quite long time to come. The key is for
He adds that few companies have built mechanisms to store the right data and to every company considering AI to begin
store that data in real-time. The intention of AI is to use an up-to-date snapshot of data to the data storage journey or strategy. n
potentially add value to a “level” rather than the transaction end state. Thus, companies
are not doing real-time, much less achieving real-time AI capabilities. “Google, Facebook
and Amazon have tens of billions of dollars to invest in AI, and even they are still in the very
early stages. They are using the data willingly surrendered by their customers to fuel these
engines – which is more data than any average business could ever hope to see – and
they still don’t have the ability to use AI for more than chatbots, advertising and a few other
specific applications.”
Firth is not alone in his opinion. Writing in The Gradient, an online magazine devoted
to tech, AI entrepreneur and writer Gary Marcus accuses AI leaders as well as the media
of exaggerating the field’s progress. AI-based autonomous cars, fake news detectors,
diagnostic programs and chatbots have all been oversold, Marcus contends. He warns that
“if and when the public, governments and the investment community recognise that they
have been sold an unrealistic picture of AI’s strengths and weaknesses that doesn’t match
reality, a new AI winter may commence.”
Another AI veteran and writer, Erik Larson, questions the “myth” that one day AI
will inevitably equal or surpass human intelligence. In The Myth of Artificial Intelligence:
Why Computers Can’t Think the Way We Do, Larson argues that “success with narrow
applications gets us not one step closer to general intelligence.”
The large multinationals are working on this, but there is still a long way to go, Firth
says. Google researchers, for example, have created software that borrows concepts from Richard Firth

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