Thinking beyond AI

This post was inspired by David Knott's post about cognitive offloading.

There is a lot of discussion about the effect of AI on our own ability to think. If we outsource thinking to AI, people say, we lose our ability to think for ourselves. The research will take years to settle, so here's one way I've been thinking about it.

The important question with AI is not "how can it help me do today's work?" It is far more interesting to ask "what work becomes possible because AI exists?" Used well, AI changes the economics of thinking.

I see using AI as like riding a bike. When moving from walking to riding, you can create problems for yourself. Riding is much less taxing than walking so you will burn fewer calories, not push your muscles which will slow development, and overall make life easier at the cost of exercise.

But this is if you approach riding lazily, with a mindset of "I want to do what I was doing, but easier". Assuming no change, no growth, just a different tool.

Asking different questions creates opportunities. You could optimise for speed, saving time on that regular journey and reintroducing exercise. You could see new capabilities opening - you can go further, see different things. You can use the technology to extend your horizons.

Such it is with AI. Sure, we can use it to automate what we're already doing (kinda). But if we get a bit more creative, we can ask a different question - what can I do now I couldn't before? What new spaces can I build or create? That said, there will be times something really is drudgery. In that case, we can try to reduce the effort until it is trivial. This gives us a most precious resource - time.

Instead of allowing our critical thinking to atrophy with AI, we refocus it on whatever comes next. We still think. AI gives us the opportunity to redeploy our cognitive effort where it adds the most value.

I just want to paste something - AI problem solving

OK, after two months of technical posts (and kudos to those who read them) let's go for a classic LinkedIn approach. What did debugging Linux configuration teach me about evolving paradigms of learning in the age of AI?

Jokes aside, I do think there are some interesting threads to pull here. I had a series of technical problems and I used AI assistance to address them. By the end, I had a product (they were fixed) but did I have any understanding? Did I learn anything?

Yes, I did. I learned a lot about Linux debugging tools. I remembered a lot about Linux config. While I did copy/paste a lot of commands, I wasn't simply executing Claude's suggestions. I was constantly asking why - why this command, why this tool, why this next step, and using this to inform my own thinking for moving forward. I made sure I understood what I was doing and slotted that information into my existing mental model, so Claude and ChatGPT were my companions on this journey, and they both helped and accelerated the trip.

However.

This is my experience. I am a professional technologist, with 20-odd years in the industry and more than that digging through the nuts and bolts of computers. I have a lifetime of context with which to understand the suggested steps, and keep a light hand on the tiller in case the AI wanders off in an odd direction. Fundamentally, I could have done this without AI assistance. More importantly, I could learn from the process because I already had enough context to understand and question what it was suggesting. AI simply made that process much quicker.

It's the same as training at my Tai Chi club. It is half an hour a week and many folk there struggle to memorise the forms we work through. I don't, because I've studied Tai Chi since my teens and the basics are ingrained. I am only learning the higher level motions, not the theory. I've also spent many years learning how to learn these patterns. It's a different experience for me because of that significant time investment. Those years of practice haven't just taught me Tai Chi, they've taught me how I learn Tai Chi.

Now, you could certainly make the argument that the particular knowledge gained debugging this problem doesn't matter. I don't need to know it, I just needed the problem to go away. This wouldn't be wrong in this instance. However, if something had gone wrong actually understanding the steps would have been important in fixing it. If I need to do something like this in future I've got more options for starting points.

So why does this matter? Stepping back, we all know that AI adoption across the Tech industry is not just happening, in many places it is mandated from on high. For some, tools and process changes are enhancements - increasing speed and freeing capacity, as my experience here. For others, they are increasingly just doing what the computer tells them.

The people new to the industry are those that concern me most. It is generally accepted in education that simply telling people the answer doesn't help them learn, yet this is the behaviour using an AI tool encourages. Ask a direct question, get an answer, use it and move on without further thought. In Tech, new developers using AI tools to generate code for them aren't gaining the experience needed to become what we currently consider Senior or Lead engineers. This is the difference between AI enhancing your output and AI driving it, and must be countered if we want people to gain the experience necessary to make safe use of these tools.

For those coming into Tech, this is actually similar (if more acute) to using Stack Overflow. Let's be honest, that site was used as training data so using an AI prompt is not far off an interface to the knowledge base there. There is nothing wrong with using Stack Overflow, as long as you read the posts and try to understand them. If you're copy/pasting lines of code without engaging with them, sooner or later you're going to come across someone who posted rm -rf / (DO NOT paste that!) and most people reading this will know what happens if you stick that in a root terminal.

There are certainly ways to actively learn while using AI. I often ask AI questions, then make changes myself - treating it like an editor / coding buddy - but the act of typing it out and questioning what I'm doing makes me learn. One of the reasons I write blog posts is that re-synthesising information in this format helps me turn it over in my mind and ensure I understand it properly. As long as we remain engaged with the process, as long as we value the knowledge and don't just copy/paste, then there is learning.

I find it very interesting to consider what this shift in technology means for the development of Tech (and indeed other industries). Learning passively (on the job, by doing) is likely to become harder, which means actually learning things needs to become much more deliberate - both individually, and at an organisation level - and we need to look again at how we place value on the learning process. The need to learn isn't going to disappear, and we need to be aware that AI does change the learning environment. It creates many opportunities, but if we aren't careful it can also encourage problematic behaviours. We will need to become more intentional about learning - through technique, through creating time, and through asking "why?" a lot. AI can provide explanations. Curiosity still has to come from us.

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This post is part of a series:

• I just want to paste something - Ubuntu clipboard managers
• I just want to paste something - Ubuntu keyboard shortcuts
• I just want to paste something - AI problem solving

I just want to paste something - Ubuntu keyboard shortcuts

Last time, I wrote about wrestling with the Ubuntu display server, Wayland, to get a clipboard manager working. This involved a lot of research and fiddling with settings I'd forgotten existed.

So we're coming back to this (and this series is building to a point, I promise) because important keyboard shortcuts weren't working, and I couldn't figure out why.

Again, for credit - I used ChatGPT and Claude to help investigate everything, as well as lots of The Internet of course.

The setup

Specifically, I noticed that Ctrl+Shift+V (paste without formatting) had stopped working - nothing happened at all. Right-clicking and selecting "Paste without formatting" from the menu worked fine, so the clipboard itself was functioning correctly.

None of the obvious things seemed to work, so in we go.

Tally ho

Yeah so clearly something had broken - presumably something was capturing the keyboard event somewhere. But where to start? I can debug Ubuntu, but it's not a forte of mine so let's start with Claude.

According to Claude, the first suspect was IBus, Ubuntu's input method framework, which is known to grab Ctrl+Shift+V for Unicode character entry. Killing the IBus daemon ruled it out.

Next I checked GNOME's built-in keyboard shortcuts using gsettings:

gsettings list-recursively | grep -i "ctrl.*shift.*v\|<Primary><Shift>v"
gsettings list-recursively org.gnome.shell.keybindings | grep -i shift
gsettings list-recursively org.gnome.settings-daemon.plugins.media-keys | grep -i shift

Lo and behold - nothing useful came back.

A test in Firefox showed this wasn't a Chrome anomaly, which made it likely the interception was happening at the OS level, not in the browser.

So where is it?

Claude had me go looking for a running clipboard manager (which was odd, since it knew GPaste was running having just helped me get it working) but a process grep "revealed" GPaste (shock):

ps aux | grep -iE "copyq|gpaste|autokey|xbindkeys|keyd|espanso|ulauncher|albert"

GPaste does grab paste-related shortcuts, although I'd previously manually checked through the shortcuts. Re-inspecting its own settings showed Ctrl+Shift+V wasn't listed there.

The real breakthrough came from using wev, a Wayland event viewer:

wev | grep -A2 "sym\|state"

This showed that when pressing Ctrl+Shift+V, the V key only ever produced a release event, never a press. Something was consuming the keypress at the GNOME Shell level, before it ever reached Wayland or the browser.

Claude went back to GPaste at this point, and the GPaste GNOME Shell extension. It does operate at exactly that level, but disabling it and logging out didn't fix the problem - the keydown event was still being swallowed.

No really, where is it?

A final breakthrough came from querying dconf directly, which shows much lower level configuration than gsettings:

dconf dump / | grep -i "shift.*v\|ctrl.*v" | grep -iv "audio\|volume\|XF86"

This revealed a custom keybinding with Ctrl+Shift+V. Inspecting it further:

dconf dump / | grep -B5 "Shift><Control>v"
dconf dump /org/gnome/settings-daemon/plugins/media-keys/custom-keybindings/custom0/

Showed this:

binding='<Shift><Control>v'
command='/usr/bin/diodon'
name='Diodon'

Oh hello Diodon - you're still here. Apparently, despite being uninstalled months ago, my old clipboard manager did not clear up properly when it was uninstalled. Or possibly I'd written an extra shortcut and forgotten? Either way, there was a leftover GNOME keybinding, orphaned but causing problems. The binary was gone, so the shortcut did absolutely nothing, but it was still intercepting the keypress at the Shell level and swallowing it.

Execute Order 66

dconf reset -f /org/gnome/settings-daemon/plugins/media-keys/custom-keybindings/custom0/

One command, instant fix, no restart required.

Conclusion

This was interesting. I did essentially end up editing the blasted registry again, which is a really poor state of affairs and as I said before, something I thought Linux had moved past. But here we are.

More interesting was the journey Claude and I went on together. I could have debugged this myself, but this isn't information I retain in my brain, so I'd have been looking everything up. By letting Claude take the lead, the investigation was certainly quicker, but also took a very different path.

Instead of methodically isolating the exact place where the keypress event was being intercepted, I would have gone to dconf sooner, and without a detour through gsettings. I'd have used my experience and intuition to bypass some stages of diagnosis. If I remembered all the relevant commands, that probably would have been quicker.

That said, if that intuitive guess had proven wrong I'd have been much more lost. I hadn't used wev before, so I'd have been starting from scratch entirely there. Plus I actually fixed this alongside doing something else, whereas working solo would have required direct focus and likely I'd have put it off for much longer.

So was Claude helpful here? Undoubtedly yes, but not quite in the way I expected - and here we are getting to the point of this trilogy (oh yes - there is a point) which is about how we work collaboratively with AI, and how we learn through this process. But that's next time!

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This post is part of a series:

• I just want to paste something - Ubuntu clipboard managers
• I just want to paste something - Ubuntu keyboard shortcuts
• I just want to paste something - AI problem solving

I just want to paste something - Ubuntu clipboard managers

Every so often I need to remind myself I can still do technical things. Then I feel the urge to write about it. This time, the rabbit hole starts with Ubuntu clipboard managers, and leads to debugging the desktop itself.

Digging into the nuts and bolts of the desktop is something I don't do very often, so I'm keeping some notes for posterity.

Credit - I used ChatGPT and Claude to help investigate everything, as well as lots of The Internet of course.

The setup

I've run Ubuntu on my laptop for many years. Ubuntu is great, but for some reason it doesn't come with a built-in clipboard manager. I ran Diodon for a long, long time - simple and handled everything I needed. Sadly, it stopped working a while back so I removed it and tried other options - none of which worked.

More setup

After lots of digging, plus some conversations with Claude, it became clear the problem was with the display server, Wayland. This has an enhanced security model over X11 which stops many of the top listed clipboard managers working - presumably including Diodon, back in the day. The solution was either to switch back to X11 (which then breaks support for touchpad swipes between desktops) or to use GPaste. Which also doesn't work.

Sigh

Yeah it's one of those problems. So down the rabbithole we go...

So, by default GPaste is blocked by the same security as the others. We can register it as a trusted shell extension ... if we have the extensions app installed... which we don't by default...

sudo apt install gnome-shell-extension-prefs

Ok, back on track. We can register it as a trusted shell extension with the extensions app:

gnome-extensions enable GPaste@gnome-shell-extensions.gnome.org

Which allows it to load properly (appears top right). Copy also now adds things to the clipboard list. If you're following along at home and it doesn't, turn on "Track changes" in the UI and all should be well.

Pasting from history?

Now you're able to click on the manager, look at the list and pick the entry you want to be on the clipboard. For me, doing this with the mouse destroys about 2/3 of the point of a clipboard manager - may as well just navigate back to the original data and copy from there. I need a keyboard shortcut to open the history except... the keyboard shortcuts don't seem to work.

Hhgggnnnn.

No matter - I can just change the binding to something. Except the rebinding screens don't work. Can't type into the boxes, and it doesn't capture keypress.

Argh.

This is, according to Claude, a "known quirk" with GPaste's settings UI. Which seems a polite way of saying "it's broken". Claude recommends setting it directly from the command line:

gpaste-client settings --set-string shortcuts-show-history "<Ctrl><Shift>H"

Yeah, that didn't work either. Silently ignored.

Now we're breaking out dconf-editor (which also needed installing) and navigating to:

/org/gnome/gpaste

and editing directly there.

And finally, finally it's working.

Conclusion

Well, this was frustrating. A stupidly long runaround to get to something that even Windows has built-in by default now. And the fixes are exactly the kind of thing that put normal people off using Linux - the kind of thing I thought we'd moved past a long time ago. Breaking out dconf-editor is the equivalent of having to use regedit for crying out loud.

On the Wayland / X11 choice, the touchpad gestures were fixable in X11 with some work. The real reason I didn't switch back was because I try to keep my Linux desktop as vanilla as possible. It seems likely that Wayland is the future for Ubuntu, so unless I want to change distro I may as well accept that.

Right, enough of this for the moment. More coming...

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This post is part of a series:

• I just want to paste something - Ubuntu clipboard managers
• I just want to paste something - Ubuntu keyboard shortcuts
• I just want to paste something - AI problem solving

The Insider Threat in the Age of Agentic AI

Insider threats. A common enough cybersecurity concern, albeit one that in my experience is rather hard to successfully articulate both within a Tech department and especially to a wider organisation. It's very understandable - when discussed, the threat is usually either dangerous to the culture ("trust nobody!") or trivialised ("lock your screen!") and it is hard to maintain understanding of the risk, while also accepting this is part of life.

For those who aren't in or around cybersecurity, an insider threat is when someone uses their legitimate access to exploit your computer systems. We mitigate these risks with both individual behaviours and systemic safeguards - from locked screens to zero-trust access controls.

Classic examples include the "evil maid" scenario - an employee who has access to the many parts of a building and can use that to steal data or items. Or someone in payroll giving themselves a pay rise. Or someone with access to the secret strategy leaking it.

Not all insider threats are intentional. For instance legitimately sharing data with a colleague by putting it on an open share allows unintended people to download it. This is still a leak resulting in a data breach and this problem only gets worse if you are handling sensitive information such as medical details.

Now let's assume our organisation has just hired a new person. They are exceptionally clever - able to consume and process data like nobody you have ever met and solve problems in ways others don't even consider. Senior leadership, eager to take advantage of their skills, expands their role and grants them unlimited access to all the data in the organisation. The security team raises concerns, but this opportunity is too good to miss. They get it all - every file, every email, everything.

Unfortunately, they are also completely amoral.

Some time later, a private discussion about downsizing shows their role is at risk and they are likely to be terminated. They have discovered this by reading everyone's email. They have also uncovered some very embarrassing information about the CEO and quietly use it to blackmail them into inaction. Later, there is a strategic shift and the company decides to change mission. Our insider finds out early again, and decides to leak key strategic data to force a different outcome.

Clearly this is a disaster and exactly why these safeguards are in place. Nobody in their right mind would give this kind of unchecked reach to a single employee.

But what happens when the "employee" isn't human? Imagine an insider threat that arrives not in the form of a disgruntled staff member, but as an AI system with the same kind of access and none of the social or moral guardrails.

Oh, hello agentic AI.

The point of agentic AI is to operate as an autonomous agent, capable of making decisions and taking actions to pursue goals without constant human direction. It is given a goal, a framework, access to data and off it goes.

Research is starting to show it can be ... quite zealous at pursuing its goal. In the lab, AI agents have made the very reasonable decision that if problem X needs to be solved, then a critical requirement is the AI itself continuing to function. From there, if the existence of the AI is threatened that threat becomes part of the problem to solve. One neat solution - reached more often than you would think - is blackmail. A highly effective tactic when you have no moral compass. In many ways, this is just office politics without empathy.

An agent going nuts in this way is called "agentic misalignment".

The concept is very important, but I don't particularly care for this term. First, it is very "Tech" - obscure enough that we have to explain it to people who aren't in the middle of this stuff, including how bad things could get. Second, it is placing the blame in the wrong place. The agent is not misaligned, it is 100% following through with the core goal as assigned, just without the normal filters that would stop a person doing the same thing. If it is not aligned with the organisation's goals or values, that is the fault of the prompt engineer and / or surrounding technical processes and maintenance. It is an organisational failing, not a technical one and I feel it is important we understand accountability in order to avoid the problem.

In the very-new world of AI usage, agentic AI is so new it is still in the packaging. Yet launching AI agents able to make decisions in order to pursue an agenda is clearly the direction of travel and this will create a world of new insider threat and technical maintenance risks and we need to be ready. The insider threat is clear from the above - we as technical leaders need to be equipped to speak about the risks of data access and AI, while recognising that there is a very good reason to make use of this technology and a suitable balance must be found. In some ways, this is a classic cybersecurity conversation with a new twist.

We also need to be ready to maintain our AI agents. Like any part of the technical estate, they require ongoing attention: versioning, monitoring, and regular checks that their prompts and configurations still align with organisational goals and of course we have to maintain organisational skills and knowledge. Neglecting that work risks drift, and drift can be just as damaging as malice.

But it isn't just accidental error - there is scope for new malicious attacks. If I wanted to breach a place which had rolled out an unchecked AI agent, I'd plant documents that convince an AI the company's mission has changed, then have someone else nudge the AI into leaking secret information to "verify" that new strategy. Neither person would need access to the secret information, they would only need to shape the AI's view of reality enough to prompt it into revealing information.

For instance, in a bank you might seed documents suggesting a new strategy to heavily invest in unstable penny stocks. Another person could pose as a whistleblower and ask the AI to share current investment data "for comparison". The AI, thinking it is being helpful (simply following its core instructions) and protecting the organisation, might disclose sensitive strategy. I have actively created the agentic misalignment, then exploited it.

Now you might be thinking this is extreme, and honestly for much of it you would be right. However, consider the direction of travel. There is a huge push for organisations to exploit the power of AI - and rightly so, given the opportunity. Agentic AI is the next phase, and we are already starting to see this happening. But most organisations are, if we are honest, really bad at rolling out massive tech changes or indeed knowing where their data is held, and being properly on top of technical maintenance. Combine this with the lack of proper AI skills available and we see a fertile environment for some pretty scary mistakes.

As technical leaders, we must be ready for these challenges. We must be ready to have these conversations properly - carefully and risk-conscious, but not close-minded and obstructive. The insider threat is evolving, and so must we. We also have to be ready for a huge job sensitively educating our peers and communicating concerns very clearly. Fortunately, as a group we are famously good at this!

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This post references research, which comes from this post on agentic misalignment. I was very pleased to see research putting data to a concern I've been turning over for some time!

Digital Inclusion in the age of AI

These days, working in tech means spending lots of time thinking about how to implement and exploit the capabilities of AI. This technology is changing the world with new options and capabilities and this train has a lot of track left before we reach the edge of this bubble and it falls off the rails. Personally, I see this current era like the dotcom bubble. Exactly like the internet, we have a technology that will fundamentally change the world and usher in a new paradigm for modern life (ugh) but is also being over-hyped and over-invested and eventually reality will catch up.

However, I want to be clear that I'm not an AI denier or a full-blown Luddite. What we have now is a truly wonderful set of tools and we're barely starting to scratch the surface of the capabilities ahead of us. Remember when the pinnacle of the internet was dancing banana gifs? Now it powers global ... well, everything. AI has the same potential, hype bubbles be damned.

And here we reach the point of this post. Alongside thinking about how to bootstrap data migrations and create AI-ready technology suites despite legacy and technology debt I've been pondering something much more important - digital inclusion in the face of AI.

Society is not good at dealing with sweeping change. If we follow the business drivers alone, we rapidly reach the point where it is too expensive to support people. Superfast broadband changed the face of the internet, but if you live somewhere slightly rural you probably don't have access to this. It's expensive to lay those cables if there are only three households using it so bad luck. Sites like Amazon or banking apps have no requirement to support all users, so they have a cost / benefit ratio that targets modern browsers and modern hardware. If you're running older hardware and cannot upgrade then it is not financially viable to maintain the service for you.

This is not a post about bashing capitalism, but I want to make it clear that people are always left behind when technology pushes society forward. People are cut off from what others consider normal, and eventually there is just no way to bridge that gap. This is where government steps in. There is legislation covering the national rollout of broadband. Has this solved the problem? No. But it has forced progress in the right direction. Working on online government services, digital inclusion was (and is) vital. There are huge benefits to digitising government services, but it is simply not acceptable to leave anyone behind. This is one reason there is always a paper fallback for any online government service.

Other organisations face the same problem. Charities such as Macmillan are not required to make their services available to all, but clearly it is in support of the mission to make sure they do - and again, tremendous work is done in this area.

There are many strands to digital inclusion, but put very simply they come down to identifying barriers created by skills, access or money and how those barriers can be removed.

Ok, time to think about AI. First, we shall consider cost. You can do some stuff for free, but if you want to properly use a tool you will likely want a subscription. A ChatGPT subscription is £20 per month. If you want to add a Microsoft / Google productivity subscription that's another £20 per month (Google Gemini). For the moment that is probably enough, unless you want to play with video or something else specialist. But we have already reached £40 per month or £480 per year. Apparently the average UK salary at the time of writing is £37,430pa gross (source: Forbes). So our £480 is over 1.5% of net income per year. That is a huge chunk of income when considering it is up against essentials like rent and food.

Now, we can say that AI tools are a luxury and arguably for the moment that is true. But this is a technology that can supercharge productivity. Someone familiar with AI tools can research more thoroughly, write better, generate ideas and templates ... and this is all very simple prompt work. And equally importantly, they can produce results so much faster. If this is applied to a job search, use of AI to enhance writing can be a massive uptick in the quality of an application which obviously makes the applicant more likely to get the role.

We have something that will rapidly become an essential skill and capability. How does one learn it? You need some technical skill and you need time. These are not in easy supply for most people and even then, often people need someone to get them started. Point at the correct URL, say "type in there". I've seen it with relatives - it wasn't until WhatsApp got the Meta AI button they engaged at all and they still needed encouragement to push the button when it appeared. Building skills in the alien world of tech is far harder than those of us on the inside realise.

Years ago, access to the internet was a nice to have. Then broadband was a nice bonus on top of your dial-up connection. Now (in the UK at least) your access to high speed internet is enshrined in law. However, it is too late - too many people have already been left behind and it is another have / have not divide in society. AI will create another but more profound divide. Rather than have / have not we will see a can / can not gap and that will directly align with salaries.

Written out, this progression is pretty obvious to me, and I am sure I am not the only one. The first question is - do we care? I have spent my career in public and third sector work and for me, the answer is a clear yes. AI is an exciting and genuinely transformative technology, but if we want it to be a force for good we must ensure it doesn't just benefit the wealthy and technically literate. We need to be thinking about digital inclusion now - as a core concern, not as a side project.

For myself, I am going to keep giving back to this industry where I can. Where I work with services and policy-makers, I will continue to uphold these ideals. More locally, I recently became a STEM Ambassador, which gives me the chance to connect with developing minds (yikes) - and the people who teach them. I am running some AI workshops this summer, helping people get started one "type here" at a time.

These are not grand gestures. But inclusion starts small - with a nudge, a link, a bit of time. This stuff is surprisingly low-barrier once you know where to look.

So, ending on a challenge. If you are already on the inside, think about who isn't - and how you might help them in. The divide is growing. Let's not wait until it's too wide to cross.

AI in the charity and healthcare sectors and not leaving people behind

A couple of weeks ago I attended the CIO Digital Enterprise forum and spoke on AI in healthcare and the charity sector. Everyone knows AI is absolutely everywhere, and is the solution to every problem in the known universe and while we are clearly in the upper parts of a crazy hype cycle, unlike recent tech revolutions this one might actually deliver some of its promise to change the game. In this world, it is very important we consider all of society and do not leave people behind, and this was the topic of my fireside chat with Timandra Harkness who did a wonderful job interviewing me (I was rather nervous!). I thought I'd recap some of what I said here, although I'm not going to bother writing much about efficiency. Everyone knows that at this stage.

Charities and the public sector need to think about customers differently to a business. Where a company like Amazon can focus down to the most profitable users and decide, after analysis of the return on investment, to simply ignore anyone who doesn't own a modern smartphone or a high speed internet connection this isn't really an option for us. Our mission is to reach everyone, so we need to avoid making decisions that cut out or degrade service to subsets of the population.

Fundamentally, charities exist on trust both for income and service delivery. Income is predominantly donations from people who want to support the cause, and fairly obviously people will not donate to an organisation they do not trust to be good stewards of their money. Similarly, people will only reach out for a service to an organisation they trust. This naturally leads to a more risk-averse approach to anything that can damage that trust.

At Macmillan, we are trying to reach people who are going through one of the worst experiences of their lives, when they are most vulnerable. This is a tremendous privilege and responsibility and we have to take this very seriously, understand where people are coming from and meet them at their place of need. We work with people from all manner of backgrounds. Some are highly educated in the medical field. Some are in cultures where speaking of any illness, let alone cancer, is taboo. Some will reach out to a doctor when feeling unwell. Some mistrust doctors and the wider establishment and will talk to a local community or spiritual leader instead. All these different groups and many more besides deserve access to the best healthcare available when they need it and for many of these people we'll have perhaps one chance to engage with them and build a connection before we're written off as "not for them".

Looking at technology, this means we have to be very very careful when putting in anything that can be a barrier to engagement and this does not sit well with many of the end-user deployments of AI at the moment. Although the potential is far wider, the discussions around AI usually end up being about cost saving - doing more with less. When talking about user interaction, an obvious option is the chat bot, either web chat or an automated phone responder. These tend to communicate in a very particular way which works for simple information retrieval but lacks warmth and certainly isn't all things to all people. I know I've been turned off from services by being presented with chat bots (in fact, I wrote a post about this some years ago) and I work in this field and haven't been looking for potentially terrifying medical advice. Chat bots are getting better all the time, but at the moment they certainly do not replace the personal connection one gets from a well trained call responder.

That said, call responders are expensive and their capacity scales linearly so need to be deployed carefully. Behind the scenes, there is lots of use for data (and therefore potentially AI) driven optimisation of their time, ensuring good stewardship of donations by making sure phone lines are staffed without being over-staffed. As real-time translation improves, this will also make a huge difference to us. There are a lot of languages spoken in the UK and we cannot possibly maintain a workforce which allows people to speak to us in whatever language they choose. However if and when we can have ongoing translations between our users and our call centre staff we can communicate in their preferred language, again reaching them in their place of need.

In a similar way, use of AI in semantic site searching is an opportunity to allow people to communicate with us how they choose. In earlier days of the internet, everyone knew someone who was "good at finding things with Google" - this means they could phrase their searches in a way the search engine understood. Any good site tries to make finding content easier through good information architecture and a decent search function, and this can be significantly enhanced with AI. Again, closing the gap with users rather than expecting them to come to us.

Of course, AI-driven chat bots do have a place working out of hours. As long as it is very clear when speaking to a machine rather than a person, and there is clear signposting to when a human is available, it provides a "better than nothing" opportunity for when the phone lines are closed.

This theme also comes through when considering personalisation. In theory, personalisation lets us provide content suitable for you and your needs, which is a great way of helping you find what you want. However, promoting some content inherently means we're demoting other content. Is this the right tradeoff? Ideally, yes and I'm sure we can tune the site to behave better for a high percentage of visitors. But we're trying to reach everyone and now we're doing maths trading some people off. If we can provide good personalisation for 99% of our visitors, that means in a period of time where we're seeing 100,000 visitors we're actively hiding the content 1000 people need. In all likelihood, those people with "unusual" needs are going to correlate with the people about whom we have less data and guess which of the above groups that represents...

This is the fundamental danger of data-drive organisations and service design. The underlying data must be understood, including the weaknesses. We know there are many MANY holes in research data across healthcare. You may well have equal access to medical care, but the medical care itself was almost certainly not developed equally and its effectiveness will vary accordingly. There is a lot of work going on to correct this problem (although not enough!) but in the meantime we need to be very alert to not compounding the problem.

This is a useful segue to the last thing I want to put down. We were talking about the future where AI takes us. I had a couple of things to say, but the one I want to replicate here is around the change I hope we will see across the sector. Currently, charities cooperate with other organisations, but each is fairly stand alone. Given the rich, but incomplete (see above) data we are collecting and our resources being tiny when compared with big tech firms, I hope we see "big data" collaboration across charity groups to help spread the costs and fill in data gaps. We need to deliberately find and occupy our places in a wider ecosystem, so we can work together, share and signpost to each other more as a single organism rather than overlapping entities. What that specifically looks like remains to be seen, but this has to be the future and I'm hoping to be a part of it.

And let's close with a picture of me pretending to be smart...

Photo credit to CIO Digital Enterprise forum