9 reasons to explore Artificial Intelligence with Dr Sean Brophy

9 reasons to explore Artificial Intelligence

16th June 2021, 2:47 pm

Few recent technological developments have garnered as much fear and optimism as artificial intelligence (AI).

Perhaps AI has captured the popular imagination because it requires us to reflect on what makes us fundamentally human, both in terms of our experiences and our capabilities.

AI presents us with stark visions of the future. Visions which can be grouped into two now-familiar over-simplifications: a utopian version where the mundane tasks of work and life are delegated to machines, and a dystopian version where automation heralds a new age of mass unemployment and human misery.

These tropes are caricatures, of course, but the promise and the perils of AI are very real.

It was the late Stephen Hawking who famously said that, “…AI will be either the best, or the worst thing, ever to happen to humanity.”

And, as fascinating as these ruminations may be, the Greater Manchester AI Foundry is focused on much more practical goals: we support the development of commercially viable products, services, and systems using AI.

Essentially, this is what Brynjolfsson and Mcafee (2017) call ‘the business of artificial intelligence’.

Here, I offer a few simple propositions on the business of AI. These points have all informed the design of a series of workshops at Manchester Metropolitan University, for the European Regional Development Funded (ERDF) Greater Manchester AI Foundry.

Our mission is to train local entrepreneurs and business leaders on the business fundamentals of technology, innovation, and AI.

Tips: (typically 10 tips and 50-100 words each. Please provide tip header then blurb underneath)

  1. Greater Manchester has a unique place in the history of AI, and the Greater Manchester AI Foundry is part of its future.

Alan Turing was an academic at the Victoria University of Manchester from 1948 until his tragic suicide in 1954. Turing’s short but brilliant career is credited with starting the field of AI, particularly his 1950 article on ‘Computing Machinery and Intelligence’.

Although much of the investment and institutions supporting in AI are concentrated in the fabled ‘Golden Triangle’ in the South of England [Cambridge, London, and Oxford], Greater Manchester is punching well above its weight on a number of important metrics (The Data City, 2020).

  1. The business of AI is growing rapidly, but this growth is unevenly spread across certain sectors, locations, and types of firms.

Although large corporates are using AI, SMEs and B2B firms are less likely to use it because they lack the expertise and data to use the technology effectively (Davenport, 2018).

In the U.K., PwC (2017) estimates that AI will lead to a 10.3% increase in GDP by 2030, but this growth will not be shared equally across the nations of the UK.

One can only speculate as to whether the AI-derived gains will be shared equally across the regions of England. Or, if AI will add to growing calls for ‘levelling up’ the investment and take-up of technologies across the regions.

  1. There are different types of AI that can be used to develop new products and services but identifying the most suitable form of AI is often the key to success.

Part of the mission of the Greater Manchester AI Foundry is developing ‘AI literacy’ amongst our participants. Helping business owners to fully understand terms like machine learning, neural networks, robotics, expert systems, fuzzy logic, natural language processing, and computer vision.

We’re interested in developing commercially viable AI products, services and systems that are responsive to the needs of customers and the market.

  1. A customer-centric approach should be the starting point for those who are interested in developing AI-enabled products and services.

Taking the B2B market as an example, a Deloitte study in 2017 found that only 32% of executives were looking to use AI to create new products. Yet, they see more potential for the technology in enhancing the performance of existing products, optimising operations, automating tasks, and making better decisions. (Davenport & Ronanki, 2018)

It is incumbent on anyone who seeks to design solutions for the B2B market to understand how AI is being used by the very businesses who will be their future customers.

For B2C firms, a customer-centric approach to innovation can take any number of forms, but human-centred design approach as advocated by firms like IDEO and Google offers a promising way forward.

  1. Many large companies are investing in infrastructure and processes to manage AI, but the same cannot be said of SMEs.

There is an open question as to whether SMEs are developing the effective processes, governance structures, and operating procedures to successfully onboard the technology effectively.

Through our workshops, we’ll discuss a number of these processes and procedures, and we’ll be paying particular attention to the ethics of AI.

  1. The transformational potential of AI has yet to be realised.

It is still early days in the development of AI for commercial uses. And not all companies, particularly SMEs, have the data that is suited to using AI.

Despite this, I am convinced that AI is the most important general-purpose technology since electricity and the internal combustion engine.

The potential of AI to transform everyday life is substantial. And although the speed and direction of this transformation is uncertain, the Greater Manchester AI Foundry will accelerate this transformation among local businesses.

  1. The impact of AI on jobs and employment is uncertain, but the nature of work will be fundamentally changed.

Writers and researchers on AI speak about the ‘augmentation’ of work by smart machines and people working together. This is a far more likely scenario than large-scale automation where machines replace human workers.

Employers ought to be preparing employees to work alongside smart machines that add value to the human efforts, whilst also minimising harm to workers, the community, and society.

  1. AI raises profound ethical questions, but ethics is the domain of human beings.

Ethics is the examination of how human beings ought to behave to other human beings. And in many ways, technology is incidental to ethics.

AI does, however, present some unique ethical challenges.

Ethical issues arise upstream at the point of data collection; they arise when AI is used for analysis. And ethical issues are present downstream in the application of AI to products, services, and systems.

At the Greater Manchester AI Foundry, we’re uncompromising in embedding ethical practices at every stage of the project.

  1. We need entrepreneurs, innovators, and scientists to ask the right questions and to tackle the right business opportunities.

Pablo Picasso once provocatively said, “Computers are useless. They give you only answers.”

What is meant by this statement is that correct answers – and the algorithms that arrive at those answers – are only as good as the questions they’re meant to answer.

The task of those engaged in the work of innovation is to ask the right questions and solve the right problems for the betterment of all.

To explore the programme and apply for the fully funded Greater Manchester AI Foundry workshops in September, visit: https://gmaifoundry.ac.uk/

References:

Brynjolfsson, E., & Mcafee, A. (2017). The business of artificial intelligence. Harvard Business Review, 7, 3–11.

Davenport, T. H. (2018). From analytics to artificial intelligence. Journal of Business Analytics, 1(2), 73–80. https://doi.org/10.1080/2573234X.2018.1543535

Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108–116.

PwC. (2017). The economic impact of artificial intelligence on the UK economy. https://www.pwc.co.uk/economic-services/assets/ai-uk-report-v2.pdf

The Data City. (2020). UK’s Top Digital Tech Cities. https://www.thedatacity.com/uks-digital-tech-cities-report-2020/

Turing, A. (1950). Computing machinery and intelligence. Mind, 59(236), 433.

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