03 November 2017

AI: the ultimate intern

by Richard Stirling and Hannah Miller

It doesn’t matter that AI isn’t as smart as the humans on your team. It is already capable of saving you time and energy by taking the easiest tasks off your hands, leaving you free to focus on more important things.

night-office-shirt-mail.jpg

 

One of the big debates of the moment is how artificial intelligence (AI) (which almost always refers to machine learning) will affect the job market. The temptation is to let one’s imagination run wild. The news is full of stories like two AIs inventing their own languages, that only 44% of adults in the OECD have skills that are better than AI, or that AI can learn in four days what it took humans 1,000 years to acquire. Hearing these, you might think that we are all about to have our jobs taken over by machines.

A fully automated future is still a long way off. Computers work best where there is a concrete decision to be made. The game ‘Go’ is a good example – it is ferociously complex to play well, but it also has a clear set of rules and parameters that decide whether a person – or programme – wins, loses, or draws the game. In most real life situations, we don’t have that kind of clarity.

Screen Shot 2017-11-03 at 11.26.10.png

 

People are still better than AI at making decisions based on imperfect information, or in situations with few previous examples to act as a guide to behaviour. At the height of the Cold War it took human intervention from Stanislav Petrov to avert nuclear war, by overriding the computers that falsely warned of a missile launch by the United States.

So where should we use an AI?

Despite its current limitations, AI has plenty to offer the world of work. We may be a long way from robots running our offices, but in the meantime it’s worth considering how AI could transform the way you work.

How can AI help you now? A good way of thinking about this is to imagine AI as a virtual assistant or intern, capable of the activities described at level 1 and 2 in the diagram above. AIs of this type are already making a difference across a number of sectors, including customer servicelegal work, and banking, taking on data processing jobs normally tasked to junior staff and interns.

For example, Linklaters are using a proprietary AI programme called LinkRFI to classify client names, capable of processing thousands of names in a fraction of the time it would take humans. Ocado, the online supermarket, uses machine learning to optimise customer relations, building a software programme capable of triaging customer emails into those requiring no response, an automated response, or an urgent response from a human.

Like an intern, AI can take on the routine, mundane tasks that occupy lots of your time but little of your brainpower. Like the best interns, it will learn quickly from its mistakes and get better over time. And importantly, like its human counterparts, an AI intern needs clear oversight to avoid it getting carried away.

However, unlike an intern, it won’t get tired. It will merrily churn through a huge volume of tasks once it knows how to do them. You can see this in action in services like photo classification from AppleFacebook and Google, new recommendations from Netflix, the scheduling assistant x.ai, or the wine advice I get from Naked Wines.

When you are thinking about how to harness AI in your team, think of it like an army of tireless interns and deploy where:

  • There is a defined outcome to optimise
  • There is data for the AI to learn from
  • There is a clear system in place to oversee how it works.

You don’t have to wait for the technology to advance. AI can help your team do more of what they are good at today, with a much smaller investment than you might think.

Get in touch if you want to find out how we can help your organisation make the most of AI.

Insights

More insights

21 April 2017

Why Government is ready for AI

12 July 2017

Five levels of AI in public service

26 July 2017

Making it personal: civil service and morality

10 August 2017

AI: Is a robot assistant going to steal your job?

19 September 2017

AI and legitimacy: government in the age of the machine

06 October 2017

More Than The Trees Are Worth? Intangibles, Decision-Making, and the Meares Island Logging Conflict

16 October 2017

The UK Government’s AI review: what’s missing?

23 October 2017

Why unconference? #Reimagine2017

09 November 2017

Motherboard knows best?

23 November 2017

Beyond driverless cars: our take on the UK’s Autumn Budget 2017

05 December 2017

Why Black people don’t start businesses (and how more inclusive innovation could make a difference)

06 December 2017

“The things that make me interesting cannot be digitised”: leadership lessons from the Drucker Forum

23 January 2018

Want to get serious about artificial intelligence? You’ll need an AI strategy

15 February 2018

Economic disruption and runaway AI: what can governments do?

26 April 2018

Ranking governments on AI – it’s time to act

08 May 2018

AI in the UK: are we ‘ready, willing and able’?

24 May 2018

Mexico leads Latin America as one of the first ten countries in the world to launch an artificial intelligence strategy

05 July 2018

Beyond borders: talking at TEDxLondon

13 July 2018

Is the UK ready, willing and able for AI? The Government responds to the Lords’ report

17 July 2018

Suspending or shaping the AI policy frontier: has Germany become part of the AI strategy fallacy?

27 July 2018

From open data to artificial intelligence: the next frontier in anti-corruption

01 August 2018

Why every city needs to take action on AI

09 August 2018

When good intentions go bad: the role of technology in terrorist content online

26 September 2018

Actions speak louder than words: the role of technology in combating terrorist content online

08 February 2019

More than STEM: how teaching human specialties will help prepare kids for AI

02 May 2019

Should we be scared of artificial intelligence?

04 June 2019

Ethics and AI: a crash course

25 July 2019

Dear Boris

01 August 2019

AI: more than human?

06 August 2019

Towards Synthetic Reality: When DeepFakes meet AR/VR

19 September 2019

Predictive Analytics, Public Services and Poverty

10 January 2020

To tackle regional inequality, AI strategies need to go local

20 April 2020

Workshops in an age of COVID and lockdown

10 September 2020

Will automation accelerate what coronavirus started?

10 September 2020

Promoting gender equality and social inclusion through public procurement

21 September 2020

The Social Dilemma: A failed attempt to land a punch on Big Tech

20 October 2020

Data and Power: AI and Development in the Global South

23 December 2020

The ‘Creepiness Test’: When should we worry that AI is making decisions for us?

13 June 2022

Data promises to support climate action. Is it a double-edged sword?

30 September 2022

Towards a human-centred vision for public services: Human-Centred Public Services Index

06 October 2022

Why You Should Know and Care About Algorithmic Transparency

26 October 2022

Harnessing data for the public good: What can governments do?

09 December 2022

Behind the scenes of the Government AI Readiness Index

06 February 2023

Reflections on the Intel® AI for Youth Program

01 May 2023

Canada’s AI Policy: Leading the way in ethics, innovation, and talent

15 May 2023

Day in the life series: Giulia, Consultant

15 May 2023

Day in the life series: Emma, Consultant

17 May 2023

Day in the life series: Kirsty, Head of Programmes

18 May 2023

Day in the life series: Sully, Partnerships Associate/Consultant

19 May 2023

LLMs in Government: Brainstorming Applications

23 May 2023

Bahrain: Becoming a regional R&D Hub

30 May 2023

Driving AI adoption in the public sector: Uruguay’s efforts on capacity-building, trust, and AI ethics

07 June 2023

Jordan’s AI policy journey: Bridging vision and implementation

12 June 2023

Response to the UK’s Global Summit on AI Safety

20 June 2023

 Unlocking the economic potential of AI: Tajikistan’s plans to become more AI-ready

11 July 2023

Government transparency and anti-corruption standards: Reflections from the EITI Global Conference in Dakar, Senegal

31 August 2023

What is quantum technology and why should policymakers care about it?

21 September 2023

Practical tools for designers in government looking to avoid ethical AI nightmares

23 October 2023

Collective Intelligence: exploring ‘wicked problems’ in National Security

23 October 2023

Exploring the concepts of digital twin, digital shadow, and digital model

30 October 2023

How to hire privileged white men

09 November 2023

Inclusive consensus building: Reflections from day 4 of AI Fringe

13 November 2023

AI for Climate Change: Can AI help us improve our home’s energy efficiency?

14 November 2023

Navigating the AI summit boom: Initial reflections

20 November 2023

AI for Climate Change: Improving home energy efficiency by retrofitting

24 November 2023

Will AI kill us all?

27 November 2023

AI for Climate Change: Preventing and predicting wildfires 

28 November 2023

Service Design in Government 2023: conference reflections

04 December 2023

AI for Climate Change: Using artificial and indigenous Intelligence to fight climate change

06 December 2023

Release: 2023 Government AI Readiness Index reveals which governments are most prepared to use AI

11 December 2023

AI for Climate Change: AI for flood adaptation plans and disaster relief

18 December 2023

AI for Climate Change: Managing floods using AI Early Warning Systems