In short, “Surviving and Thriving in the Age of AI: A Handbook for Digital Leaders” is specifically designed for busy professionals, Digital Leaders and decision makers wanting to know more about AI’s issues and impact. It is organized to allow the reader to gain valuable insights quickly and on demand. Above all, the content is grounded in real-world experience and practical applications within the context of digital transformation, ensuring its relevance to everyone who is embarking on a digital journey. Most importantly, each topic concludes with thought-provoking questions and actionable steps to guide your personal exploration of AI and its implications.

So, what’s it all about? Here’s a summary of the main elements of the book. I’m looking forward to hearing your feedback. Hope you enjoy it!

Surviving and thriving in the age of AI: A handbook for Digital Leaders 

Opinions on AI are everywhere these days. From news headlines warning us how robots will soon be taking our jobs to academic papers describing the latest image analysis advances, the promise and perils of AI are being described and debated. Yet, with the breadth and depth of AI disruption it’s all too easy to feel lost in the technical details, overwhelmed by the barrage of announcements, and confused by the implications for business and society. How can we make sense of it all? What are the key aspects of AI that will determine its impact on our lives? What does it mean for leaders and decision-makers looking to accelerate digital transformation strategies and redefine their organisations to be ready for the age of AI?

I have written this book to address these questions. “Surviving and Thriving in the Age of AI” cuts through the hype and offers a practical roadmap for navigating the exciting (and sometimes confusing) world of AI. It takes the reader on a journey through the principles and practice of AI to provide a handbook for becoming a digital leader in the age of AI.

While it covers many elements, here I’ll unpack the three key themes that form the core of the book: Separating the AI reality from the hype; Assessing AI’s impact on digital transformation; and Delivering AI-at-Scale.

Separating AI reality from hype: How to stay head with AI

Let’s be honest, much of what we see today makes AI sound like a cross between magic and science fiction. The book encourages us to step back from the sensational headlines and presents the core elements you need to develop a critical eye.

• Critical Thinking is Key: Don’t be fooled by marketing speak. Leaders must learn to evaluate AI technologies for themselves to ask better questions and place AI developments into context. A framework for critical thinking is developed throughout the book. Stay informed about advancements, but be wary of overly optimistic predictions.
• Education is Power: All of us must invest in understanding the basics of AI. Digital leaders have a particular responsibility to educate themselves and their teams. This empowers them to see through the hype and identify how AI can specifically benefit their industry. The book highlights where to concentrate your educational efforts.
• Data is King: Don’t base decisions on empty promises. The book emphasizes the importance of data-driven decision making based on a resilient data engineering infrastructure. Leaders gain deeper insights from a mature approach to data and look for real-world case studies to test, evolve, and scale their AI solutions.

Assessing AI’s impact: A key weapon in your digital transformation arsenal

The evolution of AI brings new capabilities and opportunities to digital strategies already underway. The book positions AI as a powerful tool to extend your digital transformation journey. But only if AI is considered in the context of well-governed change management practices that focus on helping people to be more efficient and effective.

• Integration is Key: AI isn’t a standalone solution. It should seamlessly integrate with your existing digital infrastructure to maximize its impact. The book encourages you to think of it as an upgrade, not a complete overhaul.
• Boost Your Capabilities: AI can supercharge your data analysis, customer service, and operational efficiency. The book provides principles and real-world examples to show how companies are leveraging AI to achieve impressive results.
• Embrace the Experiment: Change can be difficult for organisation with established products, systems, and structures. Fostering a culture of innovation is crucial for success with AI. A key emphasis of the book is to encourage experimentation, learn from failures, and use those lessons to inform future efforts.

Delivering AI-at-Scale: Expanding AI across your organisation

Making the decision to bring in new AI tools and systems is just the start. Taking an AI project from pilot program to company-wide success story requires careful planning and substantial investment. The book provides the basis for you to create a roadmap to make this leap:

• Start Small, Win Big: Adopting AI can have major implications across the organization. Don’t try to boil the ocean. Begin with focused pilot programs in controlled environments. This allows you to test the waters, iron out kinks, and understand the potential impact before full-scale implementation. But the book helps you to recognize this is only a first step.
• Build a Strong Foundation: AI will place pressure on existing systems and skills. Ensure you have the technological and organizational infrastructure to support AI at scale. This includes robust data management systems, powerful computing resources, and a skilled workforce.
• Change Management Matters: People are key to successful AI adoption. The book uses case studies to show how leaders can communicate the vision clearly, address any concerns, and provide proper training to ensure everyone is on board.
• Continuous Improvement is the Focus: AI isn’t a “set it and forget it” solution. The book emphasises the importance of continuous monitoring and improvement. Establish feedback mechanisms to track AI performance, learn from outcomes, and refine your AI applications for maximum effectiveness.

Beyond surviving to thriving with AI

All organisations are now looking to AI to reinvigorate their digital strategy. It is by focusing on these three themes that “Surviving and Thriving in the Age of AI” equips leaders and decision-makers with the knowledge and tools they need to navigate the world of AI with confidence. By understanding the true potential of AI, leveraging it to extend your digital transformation efforts, and scaling AI solutions effectively, you can move from surviving to thriving in the age of AI. This is the handbook that Digital Leaders need to help you to make that happen.

If you would like to learn more about the book, get a signed copy and see me in conversation with Macmillan Cancer Support CIO, Roxanne Heaton you can join us on 23rd July at DLHQ 

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We are calling for… [a] Local Government Centre for Digital Technology: using technological innovation to deliver reform and promote inclusive economic growth across councils.

There’s no more detail in the document, and little in the news article about it in UKAuthority either.

Now, I’ve been chatting with Owen Pritchard, who I would guess is the person behind this line, for a few years now, and I don’t doubt that he has his own, very long list of things he thinks the centre should do – so I’m pretty excited to find out in due course what that looks like.

In the meantime though, let me toss around a few ideas… what could this centre do?

1) Coordinate procurement

The first thing for me would be to start investigating how the buying power of the sector could be consolidated to produce economies of scale, and better contracts.

I’d start in the bottom right of a Wardley map, the commoditised digital gubbins that keeps councils running, and where it makes no sense to have that stuff duplicated 300 odd times across the country.

Laptops, phones, broadband connections, hosting services… all these things have councils up and down the country running procurement exercises, negotiating contracts, managing those contracts… all this could be done once nationally, or a few times regionally, with no negative impact on local service delivery.

Once that’s done, how about we move on to using that collective buying power to:

• demand better products from suppliers, particularly in the line of business system market
• consolidate social value across contracts, to create meaningful, large scale opportunities for suppliers to support local public services
• Invest in the development of new products and services, either through existing or new companies, or even local authority trading organisations

This stuff is pretty boring in many ways, but I’m putting it first in this list because I think the actual opportunities are vast.

2) Fill the security gaps

With the cyber assessment framework and the LGA’s own cyber 360 reviews, there is plenty of advice out there in terms of best practice on security. However, many councils are lacking the capacity and the capability to implement this guidance. It’s nobody’s fault, just the result of many small organisations, who through years of austerity have been unable to invest in their technical infrastructure.

This could be sorted by having support available to councils to put in place the measures needed to ensure that data and information is kept as safe as possible from a technical standpoint. Flying squads of security experts who understand the local government environment, are knowledgeable about the frameworks and guidance, and can put in place the necessary steps to make all councils as secure as possible.

3) Education, education, education

One of the most important things that a centre like this could do would be to put a lot of effort into increasing the knowledge of digital across local government. Despite various efforts in recent years, the level of digital confidence within the general workforce in the sector is remarkably low.

We need people in leadership positions to understand what is possible and what they can do to unlock this potential. We need politicians who understand the strategic levers they need to pull to ensure the right long term decisions are being made in councils around technology strategy. We need the specialist teams within local government to be up to speed with the latest developments in cloud, development, security, and data, depending on their role. We need council teams to be way more confident in utilising user-centric service design approaches.

All of this could be advanced really quickly through a properly funded and planned out strategic learning programme across the sector.

The second strand is less about formal training and more about curating existing good practice case studies and examples, and creating ones that don’t exist but really should. Part of the problem of a fragmented sector of over 300 organisations is that it is really hard for anyone to know what is going on everywhere else.

The standard of documenting the good stuff is really poor. Case studies are dominated by vendors, announcing deals and anticipated outcomes, but with no follow up. We have councils going through the process of turning into unitaries, for example, but no documented playbook on how to successfully aggregate the IT in these situations. Why the hell not!? A local government dedicate centre could have a team of researchers and content designers producing useful, findable, actionable content that would help spread the word on how to get things done.

4) Data and standards

Everyone knows about the untapped potential of data within local government, but nobody so far has had the right mix of time, money, and intestinal fortitude to get it done properly.

It means taking on the line of business system providers to open up access to the data; to help navigate the arcane table structures of these creaking software behemoths; to have in place the data platforms to aggregate, transform, and usefully visualise data; to have data engineers and scientists able to formulate the right questions and figure out how to get the answers; and to have service managers who are open and willing to become data informed, and to change a lifetime’s habit of going by hunches and guesswork.

It’s a big ask, and it’s no wonder that progress has been slow. But so many of these problems are shared by every single council in the country. A centre such as the one being propose could come up with a whole host of replicable and scalable answers to these problems.

Alongside this kind of support, there’s also a need for standards around data and a centre could help coordinate and manage standards where they exist, and support the development of them where they are needed. Just as importantly, though, the centre could provide some teeth, ensuring that councils and their suppliers are meeting these standards to enable the safe use of data to improve outcomes for local areas. The use of coordinated, collective buying power would definitely help with this!

Another area of standards where a centre could help would be to produce re-usable data sharing agreements and policy documents, to help councils collaborate with other parts of the local public service system, without the need to reinvent the wheel at significant cost, over and over again.

5) Innovate at scale

Finally, I’d want to see some collective effort at innovating in a coordinated, replicable and scalable way. Pooled resources that can reduce the risk exposure for individual councils, bringing together the best brains and ideas with the people best at delivering results, to experiment, test, iterate and improve on radical ideas for local public services.

It’s far too big a risk for individual councils to take on, and no surprise that transformational change in local government is often so incremental. The exploration of new operating models in the internet era – companies like Uber, AirBnB, Netflix and so on – have been funded by billions in venture capital. But somehow we expect councils do be able to do it, alongside running the existing services, on a shoestring?

Imagine a centre, with enough resources to be able to pull together the best service design folk, the best data people, the best technologists, the subject matter experts for specific services, all able to identify the biggest challenges facing the sector and to innovate their way through to workable solutions that can be adopted across the sector. With this kind of scale and authority, such a centre could have the clout to agitate for legislative reform where it is needed, to call for the establishment of new institutions to deliver specific outcomes, or to work alongside existing council teams to help them adopt the new models.

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As an Amazon Web Services (AWS) government transformation advisor, I’ve observed best practices that deliver success, and in this post, I summarise them. Here are 10 ways that governments use incentives to accelerate successful digital transformation. 

1. Government grants and other financial support

Governments may offer agencies a share of savings achieved through change, as well as grants, subsidies, tax incentives, or low-interest loans. These support vehicles help offset the initial cost of transformation and encourage investment in technology upgrades.

For example, the Australia Digital Transformation Agency (DTA) invests in digital infrastructure that drives the digital economy. There are tax and other financial incentives targeted at building skills and using the DTA’s digital skills passport, MyPass.

2. Capacity building and training

Governments provide training programs, educational resources, hackathons, labs, incubators, and test beds to build digital literacy and technical skills among public sector employees, businesses, and citizens.

The Canadian government’s Information and Communications Technology Council (ICTC) program Beyond the Cloud trains people and upskill employees for essential roles such as cloud architects, engineers, and administrators. Beyond the Cloud is designed to give people skills to enter the modern workplace and to give businesses and the government the capability to transform. 

3. Regulatory reforms

Governments update regulations and policies to remove barriers to digital innovation and entrepreneurship. This includes simplifying licensing processes, promoting interoperability standards, and creating regulatory sandboxes to allow for experimentation with new technologies in a controlled environment. Built-in guardrails and checkpoints increase awareness of reforms, compliance, and successful use.

Cloud-first policies are an example of a regulatory reform to incentivise digital transformation by removing blockers to commercial cloud adoption and use. In the Philippines, the Department of Information and Communications Technology (DICT) published the country’s Cloud First Policy to drive cloud adoption and “foster flexibility, security, and cost-efficiency.”

4. Public-private partnerships (PPPs)

Governments collaborate with private sector companies, industry associations, and academic institutions to develop joint initiatives and projects to advance digital transformation.

PPPs are one way to invest in the digital public infrastructure (DPI) that is an essential foundation for digital services. Ukraine’s open government procurement site Prozorro (which means transparency in Ukrainian) is an example of a successful PPP investment in DPI. The United States Agency for International Development (USAID) invested in the development of Prozorro, which is estimated to have saved Ukraine’s government $6 billion since 2017.

Examples of successful government partnerships for transformation also include the development of cloud procurement agreements, cloud-first policies, and digital marketplaces. 

5. Open data initiatives

Governments release public datasets and APIs to promote transparency, innovation, and economic development. Open data initiatives provide resources for businesses, researchers, and developers to use government data to create products and services.

Spain launched the Aporta Initiative in 2009 to open public information and promote data-based development of modern services. Aporta, backed by the provides insights on how to manage open data. 

6. Digital service delivery

Governments digitise public services to improve accessibility, convenience, and efficiency for people and businesses. They develop online portals, mobile apps, and digital platforms to access government services and information. Simpler access drives service use and increases customer demand and adoption.

The United Kingdom Government Digital Service (GDS) incentivises public sector transformation with tools it creates that remove barriers to change and improve services. These are available for reuse. An example is the GDS design system, which streamlines websites and digital content with standardized styles, components, and patterns and offers a guide on how to use them. Another example is the General Services Administration’s (GSA) 18F in the US.

7. Recognition and awards

Governments recognise and reward organisations and individuals that demonstrate excellence in digital transformation and innovation. These awards raise awareness, incentivise best practices, and inspire others to embark on their digital transformation journey.

In 2023, the European Union had more than 330 applicants for the European Digital Skills Awards across five categories. Digital government awards build culture and community and motivate people to try new things. 

8. National strategies and roadmaps

Governments develop national strategies for digital transformation to coordinate objectives and resource allocation across sectors and stakeholders. Digital strategies linked to government priorities tend to succeed. For example, the Korean Digital New Deal launched by the Ministry of Science and ICT (MSIT) has 12 goals across four sectors. Though the scope is broad, the individual goals are focused on specific government objectives and have led to South Korea being a recognised digital leader.

9. Monitor and evaluate against objectives

Governments set clear objectives and create mechanisms for continual introspection, improvement, and accountability. This helps leaders to make adjustments to keep activity on track. 

For example, Saudi Arabia’s Digital Government Authority (DGA) established indicators and a public website to provide open and transparent measurement towards its goal to move 80% of its workloads to the cloud. The DGA goal and measurement support the Saudi 2030 Vision.

10. Financial operations and spending controls

FinOps is the practice of managing spend on cloud technology. Governments establish FinOps teams, produce guidance, and provide tools to help plan, monitor, and control spending. These resources help users manage the transition from upfront investment in capital infrastructure used for traditional IT to the pay-as-you-go model used to buy cloud technology.

The UK Central Digital and Data Office (CDDO) provides guidance on cloud spending controls for all of the government. It owns and standardises controls, which reduces effort, removes guess work, and creates organization-wide best practices.

Conclusion

By implementing these incentives and strategies, governments create an enabling culture of innovation for digital transformation that supports increased user adoption, more transparency and trust, and better impacts. Incentives are a powerful mechanism for transformation. In building and executing on a digital strategy, consider how these and other incentives can be used to navigate different types of blockers to realize transformation objectives.

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But, what does that mean in reality?

The week does include in-person conferences and awards and meet-ups, but the vast majority of the week’s content remains online and I believe this remains its secret sauce. 

Why do I believe that an online programme is better than an in-person event? Well I don’t always, but whilst a few days in London or Lisbon is a great experience and for those needing to build relationships and networks with new customers is vital, for the vast majority of us this remains an impracticality. 

Also, these big “national” and “international” in the room events are usually about big tech and those with the biggest budgets fund them and drive the agenda. “No budget, no play” as they say. It can be a format that reinforces the status quo and excludes many for whom hotels and travel is either not a practical option or not allowed by their employer. 

DLWeek is nationwide and all about those who know, sharing with those who need to find out, irrespective of where the speaker is based or the audience live. 

By making the vast majority of Digital Leaders Week online and virtual we maximise that opportunity and let our audience participate from their home desk. 

However, the challenge is to organise it well and after six attempts we now feel we have got it down to a fine art. It’s about great user experience for the speaker and for the delegate alike.

Offering to give a talk is a matter of a few clicks. Our editorial team test talks for quality before loading it up and choosing a time during the week that works for the speaker. With so many talks happening in a five day period, we try hard to make sure talks on the same topics do not coincide, but with over 250 speakers that’s not easy.

What is so great is the variety. With no barrier of cost to give a talk for speakers from government, charities and academics (we do often charge a small fee to the private sector) we get extraordinary speakers offering up real knowledge, best practice and new ideas. Many do it exactly because there is no barrier for the audience to participate and they like the inclusion.

This also means that, free of the “tyranny of geography”, speakers from the North of Scotland or valleys of Wales, or experts in the more obscure areas of digital transformation expertise can find a platform and national audience that needs their know-how.

However, making all 200 plus talks easy to find, book into and experience from your home desk, is about great UX and here I believe we have it.

The key is to make all talks accessible through a single one time registration. We make the talks that matter to you findable through listing them by time, speaker and topic. You can click on everything you want to take part in and once clicked onto, we add them to your personal calendar.

We also get our partners like DWP Digital to create badges that delegates can earn during the week. Effectively, they do the heavy lifting for them by choosing, in their case, the best ten talks about Data. 

During the Week delegates start their day with an email reminding them what they booked into and we send them extra alerts just before each talk. In the evening each day they get the recordings of everything booked into that day and after the week, the whole programme is available on-demand.

All of that would just be a week of webinars, was it not for the Digital Leaders Community itself. For us and them, DLWeek is a key part of a whole year full of activity and knowledge sharing. Those who speak are seen as adding to the community and participation and feedback for them seen as part of the community’s dna. This community aspect takes it beyond just being individual talks to a collective sense of building the UK’s digital confidence together.

That’s why, for this 12th Digital Leaders Week, I shall be staying home. 

If you would like to give a talk at DLWeek 14-18 October 2024 please submit here 

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These days, we seem to mean a lot more than Ward Cunningham did when he first coined the term in 1992. As Cunningham has helpfully clarified, he was specifically referring to coding choices made in the absence of full information – information that could only be gained by releasing a version of the code and learning how it was used. The technical debt incurred in this way could be paid down by refactoring the code as its full feature set became apparent – or could be ignored, at the risk that, just as with financial debt, servicing the debt would become all-consuming: developers would spend all their time navigating an ever more complex code base, full of incrementally added and contradictory concepts.

The idea of technical debt is powerful, and intuitively appealing to anyone who has developed software, or managed or sponsored a software development project. It is so appealing that we have used it in many more adjacent contexts. I have seen the term ‘technical debt’ applied to:

• Poor coding choices made with the intention of tidying up later (the practice which prompted Cunningham’s helpful clarification).
• Systems where hardware and software upgrades have routinely been ignored.
• Systems which have become regarded as ‘legacy’ (whatever that means), and which everybody would like to get rid of.
• Choices made which contravene architectural standards (whether those standards are useful or not).
• ‘Shadow IT’ systems which have been developed in the absence of professional software practices, and brought into the scope of the technology team.

I don’t believe that this widespread use of the term ‘technical debt’ is bad in itself. The core concept – that we sometimes have to make compromises that we must pay for later – is sound, broadly applicable and has explanatory power. However, I also believe that casual misuse of the term is dangerous, and leads us to excuse technical debt or accept its persistence.

Credit, the financial concept on which technical debt is based, is a useful tool which makes our economy possible. It enables us to move value across time and space. It enables me to buy something today which I will not be able to afford until tomorrow.

But it is easy to let the habit of spending on credit get out of control, especially when you can’t see the balance and you don’t know the interest rate. Once the concept of technical debt as a conscious choice exists, it is easy to incur debt for bad reasons: the project manager only cares about this release, so we’ll test minimally and manually; the sponsor really likes this particular technology product and, well, they’re the boss; the release schedule is full this year, so we’ll push the upgrades to next year. Putting the consequences on the technical credit card becomes a habit.

Furthermore, just as most companies usually require some form of borrowing, to invest, or grow, or acquire, we can easily fall into the trap of thinking that technical debt will always be with us. Our systems will always be a bit out of date; our architecture will always be a bit of a mess; our code base will always be a bit difficult to understand. Paying the interest on this persistent debt becomes part of what we do, until it consumes or overwhelms us.

The form of technical debt that Cunningham originally wrote about was not an excuse and was not intended to be persistent: you cannot know everything about the desired behaviour of your system until you make a release, and the experience of that release will teach you that you would have done things differently if you’d had all the information. Small amounts of technical debt, paid down quickly, are an inevitable part of software development. But this is not how most organisations think about or manage their technical debt.

Perhaps one way to help us stay in control of technical debt is to ask ourselves: who are we borrowing from? In one sense, just as with all credit, we are borrowing from our future selves. But this doesn’t fit the metaphor: with true debt, there is always a lender, and it is that lender who makes us pay. I think that when we incur technical debt, we are borrowing from the systems we are building and the architectures we create. And, if we are not careful, they certainly make us pay.

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In 2023, the UK Communications and Digital Committee’s report highlighted a significant digital divide, showing that 7 million households are without broadband or mobile internet access. Rising living costs have exacerbated this issue, resulting in 1 million people scaling back or entirely cancelling their internet services in the last year. The report also emphasises a concerning trend in workforce digital literacy, with over 5 million working adults unable to perform fundamental digital tasks required for their jobs. Alarmingly, the lack of basic digital skills is projected to become the most substantial skills gap in the UK by 2030.

In an increasingly digital world, the importance of inclusivity for all cannot be overstated. Digital exclusion, a challenge facing many, especially in the public sector, hinders access to essential services and opportunities.

This blog explores effective strategies to promote digital inclusion, particularly focusing on those currently marginalised or excluded in the digital realm.

Understanding digital exclusion

Before diving into solutions, it’s crucial to understand the challenges faced by the digitally excluded. These challenges include:

• Lack of Access to Technology: Many individuals do not have sufficient access to digital devices or reliable internet connectivity.
• Digital Literacy: A significant portion of the population lacks the necessary skills to navigate the digital world effectively.
• Financial Barriers: The cost of digital technology can be a prohibitive factor for many, especially in lower-income communities.

Strategies for digital inclusion

To address these challenges, several strategies can be implemented:

• Policy Interventions: Governments and organisations can create policies aimed at making technology more accessible and affordable. This might include subsidies for internet access or providing public spaces with free Wi-Fi and digital devices.
• Community-Based Programs: Local initiatives can play a pivotal role in teaching digital skills. Libraries, community centres, and schools can offer workshops and training sessions.
• Partnerships with Stakeholders: Collaborations between the public sector, private companies, and non-profit organisations can lead to innovative solutions. For example, tech companies can donate devices, while educational institutions provide training.
• Inclusive Design: Digital services should be designed with inclusivity in mind, ensuring they are accessible to people with disabilities and those with limited digital skills.
• Awareness Campaigns: Raising awareness about the importance of digital inclusion can change public perception, alleviate technophobia, and encourage more people to get involved in bridging the digital divide.

Recommendations for digital leaders

In your role within digital transformation and operations, you play a crucial part in this journey towards greater digital inclusion. Your expertise and leadership are key in driving these initiatives forward within your Council. Here are some recommendations:

• Leverage Data: Use data analytics to identify areas with significant digital exclusion and tailor your strategies accordingly.
• Engage Communities: Understand the unique needs of different communities and engage with them to find the most effective solutions, appointing ‘Community Champions’ to support projects.
• Promote Digital Literacy: Focus on building digital skills at all levels, from basic internet navigation to more advanced digital skillset.
• Advocate for Inclusion: As a leader, advocate for policies and practices that prioritise digital inclusion.

Conclusion

Encouraging digital take-up amongst the digitally excluded is not just a technological challenge but a societal necessity. By implementing these strategies and recommendations, we can move towards a more inclusive digital future, where everyone has the opportunity to benefit from the digital revolution. It’s time to act now and ensure that digital transformation is inclusive for all.

Originally posted here

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Plan A – The agile approach

We have recently been working on developing a new government digital service. If you are familiar with government project cycles, then you will know that there are five stages to product delivery; discovery, alpha, beta (split private beta, public beta), live and retire. For simplicity, we haven’t included retire in our diagram below.

We began the project using this approach. The ‘discovery’ and ‘alpha’ phases were supported by research work; exploring the client’s problems, understanding the users and their needs and establishing how the system is going to work. Our plan was to continue with research into ‘beta’ so that we could obtain live user feedback during the product deployment. You’re expected to use agile delivery throughout the lifecycle of a service. It was during the alpha phase that our problems started. We used a scrum approach, delivering in two-week cycles and began to notice that the research was being stifled in favour of delivering something within the sprint. It wasn’t working. We needed a plan B.

When Plan B is needed

Agile became popular in the 2000s, and it felt like a revelation for the industry. Gone were the days of drawn-out projects where you would only see results right at the end of the project. With the agile methodology, success was measured by quality outputs during the delivery phase. An agile approach was great for creating software where the user could access revised and improved versions at a regular cadence. It also put developers in charge of their own workload, and it brought stakeholders closer to the action since they were involved in the day-to-day work.

Industry experts in the UX space saw a big flaw. An agile approach doesn’t work so well for research. With research, the length of time it takes is dependent on so many things. It depends on when the users are available. It depends on how much data you get. It depends on what outputs you need to create. All of these factors are unknown at the beginning and may not fit into the two-week sprint timeframe. So, a new approach was required to help make agile more UX-friendly, and that evolved into what we now know as dual-track agile.

Plan B – Dual-track agile

The spirit behind dual-track agile is that the entire team engages in two distinct work tracks; research and delivery. The research track utilises the team’s expertise to produce, test, and validate ideas that help strive towards a solution. The delivery track takes that validated idea and converts it into a usable product version within that sprint.

Everyone’s a researcher

From a research track perspective, it’s important to be versatile. Not every design cycle has to create something tangible; it may be used just to validate, or even invalidate an idea. Some loops can be short, others need to be larger. The dual-track approach makes space for the flexibility and versatility that the research track requires.

We learned how to focus on what’s viable, not what’s perfect, which helps shorten the iteration cycles. It is important to involve the whole team within the research track. For example, we had our technical architect support us in co-design sessions with users and stakeholders. Developers and testers would join us in user research sessions.

Dual-track agile isn’t perfect

No method is perfect. We encountered some key challenges. There were four large ones:

1. Getting one team into the two-track mindset isn’t easy

With dual-track agile, all the team work on both tracks. This was a tricky mindset for a few reasons; reluctance to donate time, context switching is hard work and there was apprehension around someone critiquing an area that wasn’t their responsibility, such as design or development. We overcame these barriers by introducing some ground rules to encourage constructive ideas and feedback within a safe space. We introduced technical refinement sessions to give everyone time to think and iterate. And we added visual reviews and UX reviews as checkpoints in the development process for the designers to review and discuss the progress whilst ensuring that the planned output still met the desired need.

2. Getting the two tracks to work coherently towards the product vision

Dual-track agile is a fast-paced method. It kept the project and team focused by creating and monitoring a roadmap for delivery. And it empowered us to be disciplined with what was needed now and later.

3. Scope creep

When you involve more people, you generate more ideas, which can lead to scope creep. Consciously sticking to the roadmap helped, but we needed something more. So, we adopted a ‘good enough’ mindset. Every solution was challenged as to whether it was ‘good enough’ to solve the problem. And if it was, we asked, ‘does it fit the roadmap’? If we got two yes’s we knew we could implement it and move on.

4. The ‘good enough’ mindset is hard to get into

Triad has a track record. Clients from ten years ago are still using us today. We work hard to hire brilliant people. We are award-winning. We want perfection. At first, ‘good enough’ felt like we were settling for second best. But we realised that ‘good enough’ isn’t settling for anything at all. In reality, ‘good enough’ is about delivering excellence rather than searching for perfection.

Reaping the dual-track rewards

There were lots of benefits to the dual-track approach. The stand-out benefits were:

1. User-centric design, informed by technical experts, ensures that you create something that is grounded in reality

That’s because you’ve tested something that has been validated by the user needs and built within the constraints of technology.

2. Structured creativity creates stability and confidence

Because the entire team is involved in the research track and delivery track, what you end up with, is the ability to create something that is truly deliverable. This is helped by the ‘good enough’ mentality in that you have solved lots of small problems with simple solutions that collectively end in an intuitive product that isn’t trying too hard. It doesn’t put demands on the user to ‘over-think’. Therefore, everyone has confidence in it.

3. Dual-track agile encourages a forward-thinking approach

Fostered collaboration increases dialogue between your specialists across the team. It creates a better overall decision-making process. It forces the delivery workstream to adopt a forward-thinking approach and be mindful of what problems may be on the horizon rather than waiting for them. It also helps validate the research and prevents developers delivering something that doesn’t solve your client’s problem.

It’s a wrap!

Now, in public beta, we can safely say that the dual-track agile approach worked for us. It was the ideal method for a heavy UX project that kept the scope contained within a tight timeline. We have some great learnings. It’s important to adapt your methods as the project goes on. It is ok to veer from the original Agile principles,or from what everyone else does. You’re unlikely to always get it right the first time. And that’s ok. Agile your agile process. Iterate your iteration process. And go on that journey to let research inform delivery at every sprint.

Originally posted here

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As a result, there is rapidly rising interest and use of AI in the public sector. The Alan Turing Institute survey of almost a thousand public sector professionals in December 2023 reported that almost half of them were aware of generative AI and more than one in five of them already use it.  

At the same time experience with AI, and particularly generative AI, shows the need for ethical and responsible use of a technology that can produce seemingly endless streams of text, images, or other data using large language models (LLMs) in response to user-defined prompts. 

So the UK Government’s Generative AI Framework, published on January 24, 2024, is a timely and crucial step in guiding the controlled use of this powerful technology. The UK Framework’s straightforward approach is organized as 10 principles that form a foundation for ethical and responsible AI deployment. While quite broad and high level in nature, each of these principles focuses attention on core concerns that must be addressed in any public sector generative AI use case. 

Let’s take a look at the UK Framework’s key points:

• Understanding and limits: Principle 1 rightly emphasizes the need for clear knowledge about generative AI’s capabilities and limitations. Public sector leaders must be aware of potential biases, inaccuracies, and security needs.
• Responsible use: Principles 2 to 5 delve into responsible use, encompassing legal, ethical, and security aspects. Engaging compliance professionals, mitigating bias, and ensuring data security are crucial steps towards building trust and preventing harm.
• Human control and collaboration: Principles 4 and 7 highlight the importance of human oversight and collaboration. Keeping humans in the loop for quality control and decision-making, and embracing transparency, are vital for accountability and public trust.
• Lifecycle management and skills: Principles 5 and 9 address the full lifecycle of generative AI solutions, from procurement and deployment to maintenance and skill development. Utilizing existing government resources like the Technology Code of Practice and investing in acquiring necessary skills will be critical for successful use.
• Right tool for the job: Principle 6 reminds us to choose the right tool for the specific task. Understanding use cases and evaluating tools like LLMs wisely are critical to achieving desired outcomes.

Beyond the Framework: additional considerations

From a conceptual perspective, it is difficult to find fault with the UK Government’s Generative AI Framework. Its 10 principles bring clarity to several concerns that are priorities for those considering generative AI. However, in a rapidly-evolving landscape where digital leaders face considerable daily operational challenges to deliver effective public services, the UK Framework needs elaboration. In my experience, several additional considerations could strengthen its impact:

1. Focus on impact, not technology: While the UK Framework aptly cautions against technology-driven solutions, emphasizing the need for a clear problem statement and user-centric approach would further solidify this point. The UK government’s service manual can be a valuable tool to ensure this focus on solving the right problems.
2. Continuous monitoring and adaptation: The UK Framework does highlight the need for continuous monitoring and review to ensure generative AI solutions remain ethical, unbiased, and effective. However, the costs of providing flexibility and adaptability can be substantial, which is a significant challenge that is frequently under-resourced in the public sector. The Framework needs strengthening with the addition of clear metrics and feedback mechanisms for this ongoing evaluation and adaptation.
3. Public awareness and education: The public needs to be informed and engaged in the use of generative AI in the public sector. There has to be more focus on this, with maximum transparency and accessibility of information about how the technology’s tools are used and their potential impact. Our society is only recently learning about AI’s disruptive impact on our lives and livelihoods: trust and legitimacy depend on us understanding how we may reap the rewards while managing challenges. 

With these updates in mind, I’d recommend an additional principle for the UK Framework: 

Principle 11: You build public trust through ongoing dialogue

You discuss the challenges and opportunities of generative AI openly with the public, through regular town halls, public forums, and interactive platforms.  

You encourage ongoing constructive dialogue and engage all stakeholders, including those from traditionally hard-to-access parts of society.  

With this additional principle, the UK Framework would be more complete as a guide ethical, responsible adoption of this powerful technology in the public sector.

Implementing the principles: From theory to practice

The UK Framework provides a clear roadmap, but translating it into action is the true test. 

Effective implementation starts with embedding the UK Framework’s principles into the DNA of every project. Investment in training public service professionals must cover every stage from understanding the principles to deployment. Guardrails such as checklists and decision-making matrices for every project that generative AI touches could support this.   

Furthermore, robust governance structures are essential. Public sector agencies are already appointing dedicated AI leads and ethics committees to oversee generative AI projects. These should now be tasked with ensuring compliance with the UK Framework and fostering a culture of ethical decision-making. Regular assessments and audits should be conducted to identify potential issues and ensure ongoing adherence to the principles. Transparency becomes paramount here, with clear communication channels established to inform stakeholders about how generative AI is being used and its potential impact.

In practice, the success of generative AI in the public sector requires a proactive, multifaceted approach. The UK Government’s Generative AI Framework is a welcome advance. Embedding its principles into everyday practice, instituting strong governance structures, and prioritizing transparency are key pillars for success. By taking these steps, digital leaders can leverage the power of generative AI for good and build trust with citizens and stakeholders. 

The AWS Institute has recently published an AI/ML Masterclass looking at AI in the public sector. 

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In December, Digital Poverty Alliance responded to Ofcom’s Making Sense of Media consultation, to call for online services to provide resources to customers which improve their online safety and digital literacy. In their introductory documentation for the consultation, Ofcom define media literacy as “the ability to use, understand and create media and communications in a variety of contexts”. While this definition is accurate, it encapsulates how discussions surrounding media literacy too often fail to dive deeper into what the capacity to ‘use’ and ‘understand’ media really means – and that this will vary drastically between age groups, media platforms and even the devices being used. As we articulated in our consultation response, Ofcom’s comments on how “platforms have an important role to play in increasing users’ media literacy” need to consider how this role may vary between different age brackets. For example, young people may need more support to detect fake news and protect themselves from harmful online content.

All too often, online media platforms fail to accept responsibility for user safety. The DPA’s response to Ofcom’s survey sought to highlight the urgent need for online platforms to take a more active role in educating and protecting their users from online dangers. While Ofcom asserts the review is ‘separate’ although ‘complimentary’ to online safety regimes, the DPA believes the two should be discussed in tandem to ensure media literacy by design has online safety built in as a central foundation.

We called for a more centralised approach to establishing best practice principles and ensuring these are adequately monitored and evaluated. While it is essential that services consider media literacy as part of their KPIs or OKRs, this alone is not adequate. Media literacy policies, Performance Indicators and Objectives need a consistent approach. Allowing companies to set different measures makes it difficult for these to be compared and assessed in terms of efficacy and impact. We pointed out that Universal Performance Indicators and Objectives would help to compare companies’ efforts and set universal and regulatable policy standards. Additionally, the DPA called for more consistent methods for users and third parties to raise concerns and complaints about companies which fail to implement best practice principles. Current policies allow social media platforms to dictate and implement their own standards, making it difficult or near impossible to hold them to account for failures to protect or educate their users. Centralising policy and providing clear consequences for those who fail to implement these policies would help ensure users are kept safe and help monitor and alter Media Literacy Policies as digital tools and technologies change and develop over the next decade.

Ofcom are currently assessing the consultation responses.  Media literacy by design holds so many opportunities to increase confidence and trust in online services for adults and children alike, and we look forward to seeing the policy changes that result from this work.

Originally posted here

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