I recently had the pleasure to visit the Houses of Parliament to listen in on the evidence session of the All-Party Parliamentary Group on AI about AI & Sustainability: SmartCities & Clean Technologies.
Marrying my interests in digital twin, AI, sustainability, and equitable impacts this was a fascinating event. Chaired by Stephen Metcalfe and Lord Tim Clement-Jones, we heard from industry leaders already implementing pieces of this puzzle, and enjoyed “techno-optimistic” perspectives on benefits AI can bring.
The speakers
Will Cavendish, Digital Services Leader, Arup: Smart city tech is driven by sustainability challenges. AI is a critical enabling tech in design, build and operations, and can give 30-40% energy efficiency gains.
Courtney Holm, Vice President of Sustainable Futures, Capgemini: we must consider social sustainability, and act with human intelligence before automating with AI. “Equitable urbanisation”, eg of infrastructure like 5G is needed to gain ubiquitous benefits for all.
David Elcombe, Managing Director, WindWorkX: shared about projects like CityMesh in Antwerp, and some very futuristic sounding capabilities being researched of drones, flying taxis, optimised energy use. But public engagement will be key.
Iggy Bassi, Co-Founder, Earthena.AI: described integrated climate intelligence, a dashboard for cities to monitor and adapt
Tim Kay, Director, Science and Technology Directorate, Department for Business and Trade: Long term investment and convergence of many sectors will be required.
My take-aways
It’s clear that public-private collaboration will be needed to fully realise the benefits, but what does that look like? With the huge volumes and variety of sensors, monitoring and data needed to underpin transformation, it’s also clear that building public trust is essential.
I’m also now curious how this all intersects with the future of industry (i.e manufacturing, construction) and industry 4.0, which was briefly mentioned, and provides vital materials and infrastructure for smart cities. How does the work of programmes like TransFIRe Hub and other Transforming Foundation Industries projects, on topics like enablers for circular economy, all come together in this future picture?
You can join these types of meeting too
By the way, did you know that many APPGs are open for anyone to attend meetings? You can just register and (presuming tickets are available) join.
8th January 2024 is Ethnicity Pay Gap Day. It’s a campaign calling for mandatory pay gap reporting and pay parity across ethnic groups.
The Pay Gap is the percentage difference in the average pay between group. The ethnicity pay gap compares ethnic minority communities to White British people. In the UK, government data shows that most minority ethnic groups earn less. Most notably people of Pakistani heritage earn 16% less, Bangladeshi people 15% less, and Black African people 8% less.
The pay gap can arise because of unfair pay, and also because fewer people from ethnic minority communities hold roles that attract premium pay. This plays out in our workplaces and across our economy.
Data can shine a light on inequality, and let us see the systemic disparity that exists in our society. I have found data to be an incredible way to unlock attitudes and open people’s minds. Then together with people’s stories of lived experience the case for change becomes clear.
You can only manage what you measure. Ethnicity pay gap reporting gives a basis for organisations to examine representation of ethnic minorities across their roles and levels of seniority.
Today we call on all organisations to live up to their values, show transparency and take accountability for change.
Organisations may be reticent to report their ethnicity pay gap for a variety of reasons. As someone who leads ethnicity data collection ethnicity, analysis and pay gap reporting, I can give my assurances that the challenges that may be concerning you can be overcome. If you would like to know more, please use the contact page to get in touch, or find me on LinkedIn.
Let’s start measuring, reporting, and taking action to close the ethnicity pay gap.
😶 I quit my job as Director of People Data and Insights at AVEVA 😅 … to run Inclusioneering Limited full time ✅ I joined the trustee board of BCS, The Chartered Institute for IT ✅…and the board of directors of ForHumanity, an AI ethics and audit charity 😍 I had the pleasure to work with amazing clients who continually inspire me: TransFIRe Hub, Materials Made Smarter Centre, Lucideon, VBuddies – Metaverse Tech Ltd, Scott Bradbury, EIT Food 🤝 … on projects spanning strategy development, surveys, research and data analysis, leading the Foundation Industry EDI working group, learning and development, and digital privacy, safety and equality 🏫 and with top universities including Durham, Leeds, Nottingham, Cambridge, and Sheffield 🎤 30 Public speaking engagements 👨👩👧👧 Expanded my network of outstanding associates who co-deliver Inclusioneering’s work 📃 Inclusioneering Limited was shortlisted for the StartUp Awards Social Enterprise of the Year 🏅 And winner of SME News Corporate Inclusion Consultancy of the Year 🤩 I met one of my heroes, Dame Stephanie Shirley, for afternoon tea at the Savoy (still in shock this happened! 👀) 💎 And continued to work with another, Professor Sue Black OBE ❤️ 👏 Judge for the ComputerWeekly.com Most Influentual Woman in UK Tech award ⭐ 4 visits to the Houses of Parliament, on tech, diversity and Ethnicity Pay Gap topics, and joined 1 government roundtable on AI
I owe thanks to very many people for enabling all of this to happen.
That’s the highlights reel. The reality is of course far more mixed, and I want to balance the showcase with some of the challenges that have accompanied it, because life is complex and that needs to be seen too. ⬛ Discovering the rollercoaster of running your own company full time, during a downturn in demand for diversity, equity and inclusion projects ⬛ Cutting my income by over 50%, plus no more pension or benefits ⬛ Multiple family health challenges, many still ongoing ⬛ Subsidence causing progressive damage to my home, 18+ months into an insurance claim with no resolution or end in sight ⬛ The challenge to maintain my own wellbeing from what can be emotionally intensive work, plus all the other stuff above
On balance, it’s all been worth it, and looking forwards to 2024
By Rebekah Bostan, Parul Wadhwa, and Jo Stansfield
Have you ever wondered what you can do, as an individual, to foster digital inclusion in your organisation?
Colleagues are not powerless in the adoption of AI by their organisations and are likely to play a vital role in ensuring inclusive adoption and usage. To help you Making Chance in Insurance (MCII) and Jo Stansfield have put together a list of actions individuals can take to support inclusive digital transformation and AI adoption.
AI will transform all types of businesses and is transforming insurance by increasing personalisation, reducing operating costs and supporting new product development, but we need to ensure that the adoption is as inclusive as possible at all stages of development. This includes the design, development, deployment and use of the technology and importantly its overall governance. In particular, we need to ensure that we do not end up excluding some groups and deskilling others given the current speed of digital transformation and AI developments.
“Technological progress has to be designed to support humanity’s progress and be aligned to human values. Among such values, equity and inclusion are the most central to ensure that AI is beneficial for all.”
You may or may not have direct influence in all the areas highlighted, but either way, we think you should know what best practice looks like and know where possible you can influence the development of more inclusive digital adoption and implementation.
1 )🚨Get your learning hat on – you are not a helpless bystander in the accelerated adoption of AI.
AI, and especially generative AI, provides a direction/co-pilot and even tools to undertake our work more efficiently, but humans still have a responsibility for how it is used. The June 2023 PWC Workforce Hopes and Fears Survey found that 57% of respondents felt that AI would positively support them in acquiring new skills or improving their productivity. Unfortunately, most organisations are not yet providing sufficient staff training, so it is important for individuals to start engaging with technology, such as generative AI, themselves.
Some great personal upskilling tools we have found include:
ACTION: ⚡Commit to upskilling yourself – make a weekly plan
2) 🎯Recognise the Automation Bias and value the need for a ‘human-in-the-loop’
Checks and balances are vital to minimise humans’ over-prioritising automated decision-making system results over their own judgement, especially as automation is only likely to increase.
Be aware of the human tendency towards “automation bias”, which means we place trust in automated systems, even when there may be information available that demonstrates they may not be trustworthy. Consequently, we may follow suggestions or actions by the system uncritically and fail to take into account other sources of information. Alternatively, we may fail to notice warning signs from the system because we are not monitoring it with sufficient diligence.
ACTION: ⚡Be aware of the risk of falling for automation bias. In your interactions with AI systems, be diligent in monitoring the system, know its limitations, and seek other sources of information to verify the outputs.
⚡Find out what checks and balances your organisation is putting in place to minimise automation bias – and where you find these may be lacking highlight the issue.
3) 🌈 Accept that inclusive digital transformation requires multiple layers of defence (starting with technical operations and oversight, then moving to audit)
Organisations have three main layers of defence to ensure inclusive digital transformation. It is likely that as an individual, you will be directly or indirectly involved in one of these layers of defence. Taking time to understand what your organisation is doing to support these defence layers will help you to understand where there might be gaps and or ineffective defences.
Layers of defence
ACTION: ⚡ Be willing to ask challenging questions about your organisation’s barriers of defence, whatever your level in an organisation. Here are some suggestions:
Technical operations: How are we assessing that the system is operating as intended on an on-going basis, and managing the risk of unintended consequences?
Oversight and accountability: What is our data ethics framework for how to use data appropriately and responsibly? If you are part of an ethics committee, ask: Do we have sufficiently diverse inputs represented across technical and data ethics skillsets, and across our stakeholder community?
Audit Do we have sufficient transparency and maturity of approach to enable an effective audit?
4) 📲Minimise Garbage in – Garbage out
AI has the risk of reinforcing our own prejudices because its outputs can only be as good as the data they learn from, which often includes inherent human biases. However good the machine learning model, with poor quality data inputs, the model will learn incorrectly and produce poor quality results. “Garbage”, or poor quality data, can include inaccurate data that is a poor representation of its target, incomplete data, inconsistent data, and data that is not valid for the purpose it is being used for.
ACTION: ⚡Support the reduction or even elimination of data biases by being a strong advocate for data testing and evaluation of training data and ensuring that systems are put in place for continuous monitoring.
⚡Report adverse incidents, don’t assume others will, and if your organisation doesn’t have a reporting system in place, advocate for that.
5) 🛡️Understand why protecting your and other people’s data is important
We live in a world where websites and other services are continuously requesting access to our data, and most of the time we provide it unthinkingly. Our data has become like an alternative form of payment, a cost to get access to some service.
But we don’t necessarily need to click “yes” to get that access, and there are good reasons why we should keep our personal information private. Keeping your information private helps to protect against identity theft, keeps your financial information safe and protects you from possible discrimination.
ACTION: ⚡Read your organisation’s Privacy Policy and understand how you can report misuse
⚡Learn about your rights and responsibilities when it comes to personal data – you can find a great resource here.
6)💡Support successful adoption and usage of AI by fostering cross-organisational intergenerational and intersectional dialogues
Intergenerational and intersectional dialogues on adoption and usage are important to enable effective and inclusive adoption. Activating cross-organisational information and skill exchanges can reduce uncertainty and bias to ensure a more successful adoption of AI. This can include Reverse Mentoring, where younger employees can teach senior staff about new technologies and use cases. Intersectional workshops are another important way to bring together employees from different age groups and communities to solve business challenges, including inclusive AI adoption.
ACTION: ⚡Look for opportunities to enrich your understanding of the impact of AI usage and adoption by calling for intergenerational and cross-organisational dialogues within your organisation.
7)🛠️ Increased tech-focused hiring is likely to exacerbate existing diversity gaps and even create an ‘age gap’ – counter this by advocating for colleague upskilling
Whilst organisations are likely to substantially increase their tech-focused hiring over the next few years, the scale of need means that existing staff will also need to be upskilled/reskilled. McKinsey notes that hiring an employee can cost up to 100% of their annual salary but upskilling/reskilling costs under 10%. A focus on upskilling existing employees is also likely to support the closure of diversity gaps, as pure tech hires tend to still be less diverse than the general population. Reskilling can also prevent an ‘age gap’ appearing where older workers are effectively deskilled and prematurely exit organisations.
ACTION: ⚡Advocate for more AI upskilling and reskilling opportunities across all departments and levels so no one is left behind.
MAKING CHANGE IN INSURANCE
We are an inclusive and supportive group of insurance and technology-focused change makers who have regular challenging conversations about diversity, equity and inclusion. We then share our insights with the wider insurance and tech community. We would love you to join us at our next event – please contact Rebekah Bostan, Caroline Langridge, Areefih Ghaith or Parul Wadhwa for further information.
The above action plan was influenced by an MCII discussion in October 2023 where we explored actions individuals can take to foster inclusive AI adoption and digital transformation within organisations.
As a former techie, I have always loved data. Data analysis is like exploration. It’s a journey of discovery as something previously concealed, but often hiding in plain sight, is revealed.
People data is no different in this regards.
I started working with people data and analysis almost 10 years back. I was an employee, in a technical role at a software company, and with support of our CTO and head of HR I volunteered to analyse our people data through the lens of gender.
To find significant results that we could act on was exciting. I did find those results. And we did make positive changes. But it was also shocking. I could place myself within the findings, and all of the implications implicit in that for my future path. That brought a whole host of feelings.
There is huge responsibility to working with people data. Responsibility for data protection, making sure privacy is protected and data is only used for its intended purpose, by people authorised to do so. Responsibility to clearly communicate what data is collected, and why. Careful consideration to how we communicate about results, ensuring there is a clear plan of action to address disparity.
We must always remember that data alone never tells the whole story. Beneath those data points are people’s lives and experiences.
When I share findings from data, what I hear back are people’s stories.
Data is a powerful tool to highlight those stories that need to be heard. Used well, data gives context. It sheds light on what’s systemic, helps show what’s important and direct where to take the most impactful action.
👀Here’s how it happens, what to be aware of, and how we need to manage all types of algorithmicdecision making.
Back early in my career, I was settling in to a senior software engineer role at a new organisation when they put our entire team at risk of redundancy. HR shared that they would be using a decision making tool that assessed the way we’d used leave – favouring people who took it as long chunks, rather than small pieces. This was meant to correspond to productivity, somehow.
I suffer from migraines, and can lose up to 2-3 days per month being ill – usually resulting in single days off. I was terrified of what that meant for my chances.
But this wasn’t just me. There are myriad other reasons this algorithm could discriminate, impacting people who
💊Need to manage their health considering long term illness or disability
🤗 Care for children, parents and other dependents
🙏 Celebrate religious festivals that aren’t observed by the dominant culture
I give credit to my then employer for their transparency in the process, and swift rectification when alerted to the issue.
❓But what happens when we automate these processes?
⚠️ Automation both speeds them up and scales them out. They happen faster, and at greater scale.
⚠️ And we may lose transparency and cut out the human in the loop that oversees them.
It’s important we carefully examine processes with algorithmic decision making – any that follow a strict set of rules – for embedded bias, automated or otherwise.
PLUS Always be sure to ✅ Be transparent ✅ Keep oversight and assign accountability ✅ Make sure decisions can be explained ✅ Have a process to raise concerns
Especially post-covid, with greater flexibility in our work patterns – are you certain that flexibility that’s enabled and encouraged in one way isn’t punished by some other process or system?
Skillsoft’s 2023 Women in Tech report shows job satisfaction is falling for women in tech, despite firms’ increasing focus on diversity, equity, and inclusion. What’s behind it?
We link this to the Agile Inclusion Paradox: Although Agile methodologies, heavily used in tech, appear to reflect some good practices for inclusion, women and people from minoritised ethnic groups still experience significant challenges
↘ Women are often steered towards less technical work, but this tends to seen as less important by tech teams, leading to barriers to progression for women
📉 Jo’s research of tech teams found people from minoritised ethnicities to have lower job satisfaction than white people, and this appears to be due to feeling lower autonomy and ability to carry out work their way. Note this is entirely contrary to the Agile values, which empahise empowerment
🌟 YET the research also shows women and people of minoritised ethnicities have GREATER career aspirations than white people and men, and have the qualifications to back it. We have huge untapped potential in our teams.
So what do we do? Solutions are needed at all levels, and these findings emphasise how important it is for tech managers to take an active role to contextualise DEI and put it into practice in their teams.
I’m still pinching myself to have had the opportunity and privilege to join a government AI roundtable yesterday, focussing on the proposals in the AI Regulation White Paper. It was great to join a diverse group of leaders – as one of us said, each bringing a different piece of the jigsaw puzzle, but with great alignment across us.
My perspective
⭐️Although AI is new and rapidly developing, situations of powerful global organisations, intense commercial pressure, and fragmented regulatory landscape are not. Think Deepwater Horizon disaster in 2010. Lessons were learned then, resulting in regulatory reform and industry-wide transformation to establish a culture of safety.
⭐️Our risks from AI are not in the futuristic AI domination scenarios, but already present in the disparate impacts and harm to underserved and vulnerable communities we see happening now.
⭐️Let’s learn lessons now from other industries, to avert AI’s Deepwater Horizon event. We must move quickly to strengthen and clarify regulation and establish a culture of responsible innovation.
⭐️In the interim, incentives are needed for organisations to prioritise responsible, inclusive innovation. In Inclusioneering’ equity, diversity and inclusion practice, we see UKRI funding embedding EDI requirements to be an effective catalyst for organisations, who are responding positively, and innovatively, to embed EDI into their work
⭐️Diverse inputs are needed to fully understand the risks and impacts, as well as opportunities – across all stakeholder communities. I recommend an inclusive design approach to development of regulation
I will be spending time to write papers on these thoughts, so more to come on all these topics. Drop me a message using the contact form or in the comments if you’d like to receive a copy. Which are you most interested to explore more deeply?
In the conclusion of this two-part interview, Inclusioneering founder, Jo Stansfield, joins Bella Ikpasaja in a wide ranging discussion of all things inclusion and diversity in tech.
Listen in to learn:
Tools that Agile can offer to organisations to develop inclusive cultures
For the creative industries, how tech can inspire leaders and hiring teams
Hopes for the future of AI
What we’re seeing “on the ground” regarding digital skills
Looking ahead 10 years, how we see the social impact of tech evolving
If you prefer to read, you can find the the full text for this part of the interview on Bella’s medium blog.
And don’t forget to check out Part 1 if you missed it!
Inclusioneering founder, Jo Stansfield, joins Bella Ikpasaja in a wide ranging discussion of all things inclusion and diversity in tech, as the inaugral speaker in her series of interviews with writers, organisational psychologiest and diversity and inclusion practitioners.
Listen to Part 1 to learn:
What inspired the creation of Inclusioneering
How Jo’s experiences returning to work after becoming a parent ignited her passion for DEI
How diversity impacts business outcomes
Effective ways to boost STEM skills for underserved communities
Shifts in tech and DEI that could play out over the next 5 years
If you prefer, you can read the full interview on Bella’s medium blog.
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