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4 min read

Making AI explainable, manageable and justified in the UK public sector

By Mind Foundry on Oct 21, 2022 10:30:00 AM

Mind Foundry recently hosted 'Defining Ambitions: The Future of AI in Public Sector', an invaluable virtual learning exchange for the public sector. Delivered in partnership with GovNewsDirect, the session's objective was to explore the possibilities for AI innovation within public services. It is fair to say that many organisations are only just beginning to use AI and machine learning; although growing, the number of organisations that rely on it as a core part of their operations is still relatively small, but those that do are drastically outperforming their peers. So, what does the future of AI hold in public sector organisations?

Topics: public sector High-stakes AI Responsible AI
4 min read

Collaborating With Partners to Push Quantum Computing Forward

By Nathan Korda on Oct 6, 2022 12:49:20 PM

(This piece was originally published as a guest post for The Quantum Insider)

Topics: Quantum Computing High-stakes AI Signature Intelligence
7 min read

HumBug 2022: Detecting Mosquito Signatures with Machine Learning

By Alex Constantin on Sep 22, 2022 12:16:49 PM

 

Helping the fight against malaria

Mind Foundry co-Hosts HumBug 2022, as part of the ComparE challenge, bringing together the greatest minds to help solve one of the world’s most important problems. The goal of the project is to use low-cost smartphones to detect the characteristic acoustic signatures of mosquito flight tones, helping understand the presence of potential malaria vectors. The goal of the Mosquito sub-challenge at ComparE was to develop algorithms to detect mosquitoes within real-world acoustic field data.

Topics: Important Problems High-stakes AI Signature Intelligence
2 min read

Mind Foundry named in ‘Ethical AI startup landscape’ by EAIGG

By Frankie Garcia on May 16, 2022 2:41:07 PM

Mind Foundry are thrilled to have been included in the ‘Ethical AI startup landscape’ research, mapped by researchers at the EAIGG (Ethical AI Governance Group), who have vetted nearly 150 companies working in Ethical AI across the globe. This important research by the EAIGG is being conducted to provide transparency on the ecosystem of companies working on ethical AI. 

Topics: Ethical AI Explainable AI High-stakes AI
5 min read

Let's use AI responsibly to discover where to place EV charge points

By William Chapman on Apr 1, 2022 8:30:00 AM

Between 2006 and 2010, there were 1,096 registered electric vehicles (EVs) in the UK. Since 2010 that number has exploded, and today there are an estimated 400,000 EVs on UK roads, not to mention more than 750,000 plug-in hybrids (PHEVs). With new technology inevitably comes new obstacles and complications and as EV numbers continue to soar, the provision of charging points to keep up with demand across the country is essential. However, recent figures suggest a growing disparity between the number of EVs and the level of charge point infrastructure, as well as a “regional divide” within the distribution of this infrastructure. The situation calls for a different approach to how EV infrastructure is implemented to ensure that, as more people switch to EVs, everyone who needs to access a charging point can do so, regardless of any geographical or socio-economic factors. Mind Foundry’s work in this field aims to provide the solution to this growing problem at a time where the UK government has just committed £1.6 billion to expand the UK's charging network under their new Electric Vehicle Infrastructure Strategy.

Topics: Ethical AI Explainable AI High-stakes AI
5 min read

Performance that’s measured against the things that count

By Mind Foundry on Dec 30, 2021 9:00:00 AM

It’s no longer enough to measure model accuracy. Ethics, explainability, and wider performance are key KPIs that must be considered as equally crucial priorities.

Topics: Human • AI Collaboration Explainable AI High-stakes AI
6 min read

World Mosquito Day: Fighting Malaria with Machine Learning

By Dr. Davide Zilli on Aug 20, 2021 4:18:03 PM

August 20th is World Mosquito Day. A day to raise awareness about the diseases carried by mosquitoes and highlight the scientific innovations that are emerging to help us reduce the suffering caused by the world’s second most deadly animal. 

Topics: Human • AI Collaboration Explainable AI High-stakes AI
13 min read

Approaching Ethical AI Design: an insider’s perspective

By Joanna Crown on Aug 2, 2021 3:00:00 PM

I would be surprised to find anyone who works in the tech sector, especially if they’re working with data, who hasn’t seen a significant emphasis on ethical applications of AI, or “doing AI ethically” (even the Pope has got involved!). Conferences, research, blog posts, videos, thought-starters are all - quite rightly - honing in on arguably one of the most important considerations of the 21st century: how do we build AI to the benefit of humankind?

To some aspiring to answer this question, this might signify decades’ worth of research. To others, it’s millions of hours of person-time in algorithmic design or troubleshooting software. The responsibilities to getting this right extend beyond this to policy, regulation, education, investment… the list goes on.

But the list isn’t the only thing that goes on; as I’m writing this, thousands to millions of companies around the world are grappling with adopting AI right at this very moment. They don’t have decades or even years to play with… they need it now. As I mentioned in a previous blog post, there’s a race on to get the most out of AI adoption before it’s too late. Currently, in the UK alone there are over 1400 high-growth AI startups and scale-ups, and this doesn’t even count the vast swathes of commercial and public sector adopters outside of the AI industry. This is a real challenge.

So how can you do it ethically? Or responsibly? Or is that even technically possible right now? Let me answer by addressing some of the most common questions that we’re posed at Mind Foundry.

Topics: 3 Pillars Ethical AI High-stakes AI
4 min read

The AI adoption paradox: can cautious adoption reap maximal benefits?

By Joanna Crown on Jun 10, 2021 4:06:16 PM

In the race to adopt AI, there is a flurry of activity happening in boardrooms and technical teams across the country. AI, which even a few years ago seemed to be the preserve of a vanguard of highly innovative companies, has suddenly become a prerequisite for organisations in every sector. Perhaps the stern warning from McKinsey’s 2019 report is ringing in their ears, that “Front-runners [...] could increase economic value by about 120 per cent by 2030” whereas “Laggards, who adopt AI late or not at all, could lose about 20 per cent of cash flow”.

It appears easy, then, to stay ahead of the curve and reap the financial benefits you need to adopt AI. Yet, according to MITSloan 2020 AI Global Executive Study, it’s not quite that simple, and only 10% of companies are obtaining significant financial benefits from AI technologies. 

So, why is that the case?

Topics: Human • AI Collaboration Explainable AI High-stakes AI
4 min read

A route to more reliable, forward facing solutions with active Human • AI Collaboration

By Alistair Garfoot on May 27, 2021 4:00:00 AM

As machine learning (ML) capabilities advance, and with the advent of widely available low-cost cloud computing, AI will inevitably be applied to a wider range of more challenging problems, including those that affect the outcomes for millions of individuals throughout society. In high impact, complex settings, it simply isn’t realistic to train a model up front with a single batch of training data and expect it to perform well in all possible scenarios - such a naïve approach will almost certainly fail to capture some of the underlying nuance and edge cases of the situation, leaving gaps in performance and risk of failure during use. Active learning provides a promising way around the issue, empowering the AI to learn from human teachers in uncertain or novel settings and on new data. This architecture allows human experts to impart knowledge gradually as and when they become aware of AI shortcomings, improving performance through teaching and demonstration.

Topics: Continuous Meta-Learning Human • AI Collaboration High-stakes AI

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