Category Archives: Smarter Cities

What is effective ethical governance?

In mid-August I attended an “Ethics and Automation” panel run by HMG’s Automation Taskforce, and hosted by Katie Rhodes, Senior Policy & Strategy Advisor; this is a rather delayed part 2 of my thoughts from the session.

The second speaker was Dr Brent Mittelstadt of the Oxford Internet Institute and Alan Turing Institute. His belief is that only when you can answer the following three questions you can have effective ethical governance:

  1. What is legally required?
  2. What is ethically desirable?
  3. What is technically feasible?

AI has the potential to derive inferances about private life protected characteristics that could be used for online advertising, for example. We know that is technically feasible. It’s definitely legally and ethically dubious.

As many will know, we have a ‘black box’ problem. Often AI is designed in such a way that it cannot be or is not explained. Where decisions have been made (e.g. not to offer a loan, to increase car insurance, etc.) we have to be able to explain what has been done, and to people who are not technical too.

Brent talked about the following paper in the Harvard Journal of Law and Technology 2018, which suggests that making counterfactual explanations can be useful. For example, as a consumer who has a loan application rejected, the bank should instead tell you what would need to be different in order for you to get that loan.

Brent also introduced the need for ethical auditing. As he said:

“Principles alone cannot guarantee ethical AI”.

They are a good starting point, however. Katie took us through Google’s 7 principles, including ‘be socially beneficial’ and ‘be accountable to people’.

As you’d expect, IBM has a set of “Principles for Trust and Transparency” and a longer paper on “Everyday Ethics for Artificial Intelligence“. That paper discusses and provides suggested actions in 5 areas:

  • Accountability
  • Value Alignment
  • Explainability
  • Fairness
  • User Data Rights

Essentially, ethics is everyone’s responsibility, and we have to embed it in right from the very start, through to the very end, of whatever we are creating.

Then, moving from principles allow, Brent shared with us that the Social Science Research Network has been considering how to audit how we implement, measure and govern AI.

Brent added a couple of cautionary remarks to close: models need to be trained with local data, and when we are building a solution, do we really need to use AI within it? (That is, when we have an AI hammer we have to be careful not to just see everything as nails!)

Let’s not forget why we are doing this though. AI has great potential to transform public services and help join up delivery. Bethan mentioned that AI can be put to good use, tackling misinformation online. Brent suggested that we can use AI as a critical mirror, to hold our personal biases to account.

For part 1 of this session, see

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“There’s nothing like a crisis to make long term change”

At #ThinkGov2020 last week Ginni Rometty, IBM’s Executive Chairman, had a conversation with Jessica Tisch, Commissioner of the Department of Information Technology and Telecommunications (DoITT), NYC. At one point Jessica made the statement I’ve borrowed for this blog’s title.

It’s so true.

For a bit of background, Jessica Tisch moved into this role earlier in the year, and had 3 months to get to know what was happening internally and how it worked. Then COVID-19 hit and it was a baptism of fire for her. Firstly, she had to take the city’s workforce and get them ready to work from home, setting up remote access and MFA, distributing a great many laptops and such like.

The second phase for Jessica has been working with agencies to help them deliver traditional services and new services. For example, when people couldn’t leave their homes this left 1 million people food insecure. Her actions meant that meals could be delivered direct to people’s doors. Today they deliver 1 million meals a day. They built the service in a weekend. Folks can sign up online or call to register. They put the city’s taxi drivers – whose businesses had plummeted – to work. In Jessica’s words:

“we created a free Uber-eats in a weekend”.

It just shows what we can do when we have to – and how we can be imaginative when we have to. One of the challenges I have is making the time to think, to be creative. Anyway, I digress…

Jessica also told a story of which I am particularly proud. NYC has 1800 state schools with 1.1 million students. Whilst digital can be such an enabler, in the words of Ginni, it can create a “bigger have/have not society”. Approximately 1/3 of these students did not have access to an internet-connected device and therefore wouldn’t have access to education at home. NYC reached out to many suppliers for help; 3 stepped up. Apple provided 300K iPads. T-Mobile offered unlimited data plans for under $8/month, which made it affordable and achievable. IBM provisioned all those 300,000 iPads so they arrived with the students equipped with every app needed to support the remote learning curriculum, which meant they were ready to use out of the box. Now the most underserved can be included.

Ginni talked about what one Governor had said – there will be no more snow days! Now when it snows the students will be able to access their learning from home. I suspect there will be disappointment there!

And from what Tisch said, this new scheme is here to stay.

Ginni finished with some words that really struck me:

“Now is the time for leaders to lead with both their head AND their heart; the head deals with the mechanics, the heart will help deal with the systemic issues … we will have a chance to build back better.”

Then she closed saying that the crisis has show that we can find:

  • New ways to work
  • New ways to partner
  • New ways to fix some of what have been intractable problems (such as disease, work, social inequality)

Lets rise to that challenge!

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Don’t be afraid…

… to get it wrong.

That was another conclusion from a Smarter City workshop and I think it’s so important.

Not every good idea will work in every area in every city.  But not every idea that fails in one area will fail in another too.  So don’t be afraid to trial things.

After all, it can be expensive and hard to implement a solution city wide, especially when so many of those that are in the name of sustainability come with results that can be hard to quantify in advance.  So, try them out in a couple of areas; a Proof of Concept is not a bad thing.

Then understand why an idea was successful, or why it was not.  And keep a record.

Of course, wouldn’t it be nice if you *could* predict whether something will work?  And that’s where predictive analytics comes in.  Wikipedia’s definition is “Predictive analytics encompasses a variety of techniques from statistics, modeling, machine learning, and data mining that analyze current and historical facts to make predictions about future events”.

So, a local authority can use a variety of data (e.g. the demographics of where a solution is be applied, asset management in the area, historical data about similar solutions in this city and others) to model the implementation of the solution and the likelihood of its success across the city.  A small investment up front in the analytic solution can mean resources are better applied to sustainability: whatever shape those resources come in (funding, people, tools, etc.).  Spend wisely to spend even more wisely.

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Two for the price of one

I’ve been thinking about this ever since I sat down in a workshop with Sustainable Glasgow to discuss the future of the city centre in Glasgow and what changes are required, with limited resources, to cater for future needs.

The climate is changing, and it’s likely to get wetter and warmer.   Anna Beswick, of Adaptation Scotland, presented on the subject, and some solutions which assist.  Take a look at their website to find out more.

What jumped out at me was the need to implement solutions that can address more than one problem, thus maximising any investment.  For example, green walls and roofs assist with CO2 challenges, but also provide a level of insulation which reduces fuel consumption and therefore costs to domestic households, and to businesses, and carbon emissions by the energy providers.  Of course, this would not be appropriate for every property, but where applicable more than one challenge is being (in part) addressed by one solution.

I know less about these non-technical solutions than ones which are provided by technology, but I believe the principle applies to technology also.  One of the benefits of a system such as IBM’s Intelligent Operations Centre, is that it is a platform which allow reuse of technologies which have been applied to one requirement of a city – and of the learnings from that technology – for additional requirements of the city.  For example, it can be used to integrate asset management of roads and demographic data (typically data held by different functions in a local authority) so that it is possible to work out which roads and pavements should be gritted first in winter based upon the people that use them.  The next step could then be to integrate with CCTV provided by organisations external to the local authority to monitor traffic on the roads, and enhance the gritting plans based upon that.  (Ordinarily this example would be appropriate for this time of year, but perhaps I need to change this to dealing with flooding and floodwater instead.)

Two (or more) for the price of one is always an attractive proposition.

The challenge now is assisting cities with how to allocate cost internally when one solution helping more than one department…

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I’ll be talking about Fuel Poverty in December

In 2011 I had the privilege of being a part of an IBM Smarter Cities Challenge team, a team deployed to Glasgow to tackle the issue that is Fuel Poverty.  Making our goal “affordable warmth” we recommended a long list of actions for Glasgow, and not all of them were based on technology, but about collaboration and sharing experiences.

I’m going to be talking about this at an event for BCSWomen in Scotland on 6th December, in the early evening.  So, save the date in your diary, and I’ll add a post here when the sign-up page for the event is ready.  In the meantime take a look here

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Small steps

I’ve been thinking about the “how” of Smarter and reading the vision for Smarter Cities at is an inspirational one. But for those who already have commitments on resources (people, budget specifically) then the approach to Smarter can be achieved with smaller steps.

Let’s think about a single view of the citizen and what that may mean. A local government will comprise of many departments and for one citizen, lets call him Dave, each department may have their own copy of his contact and personal details. It is quite possible that one department will have more than one record for Dave, perhaps one with an old address and one with a newer one. And neither of those records may be as up to date as one held by another department. If Dave calls in, who do they think they are talking to? Can they allow him to access services online and be sure they are providing to the right Dave? Do they offer the same services to all the different versions of Dave?

But, we’re taking a small steps approach so we can’t rip out these IT Systems and start again, trying to consolidate into one. After all, there could be reason for having many different systems. What we need is to implement a master data management layer between systems or components that request citizen data and the databases that store data. MDM can interrogate the various data sources and present one consolidated, and more accurate, view of Dave. A view consistent for all departments.

We can increase certainty that Dave will be offered the right services, charged correctly for council tax, given the appropriate benefits and so on.

Perhaps with this single view the next step is to provide multi-channel access to the same services.

However, a local government may prefer a first step to be focused on internal operations. IBM’s Intelligent Operating Center enables a city leader to have a view of the performance of the local government and the city. The council could monitor how waste disposal is performing or how traffic is flowing on the city’s roads. But, if we are thinking in small steps it may prefer to employ intelligence capability, such as that provided by IBM Cognos to interrogate data and tackle Absenteeism and the associated costs. It can identify if the same people are continually off sick at the same time, or regularly after certain sporting events. But the patterns identified will not always be such. It could be possible to identify others not necessarily associated with questionable behaviour. What if a local government came across patterns which would indicate a member of staff had depression? What are the ethical implications?

So, not everything need be done in a big bang. It’s quite possible, and often preferable, to take smaller, yet still significant, steps to becoming Smarter.

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A few thoughts on the “cities” of “smarter cities”

When I first thought about what the “cities” of “smarter cities” might mean I fell into the trap of thinking about local government and the related connotations. But I suspected that was just a little short-sighted.

So, I decided to think about what a city is from the perspective of a citizen, and of someone who uses a city. What is a city to me? For me, it’s the place I live, whether I own, rent or something else. It’s the place where I pay my council tax so that it’s kept clean and tidy, so that my bins are collected and the city council can work towards sustainability by implementing recycling, and so that I get a continued water supply to my property. So that parks are looked after and safe places to be. Which leads me on: the city is the place where I want to be safe (having been mugged once I can assure you it’s no fun), where I might need to be treated for an illness, and may need to receive care in my home too.

I need to be able to travel around the city (let’s avoid a debate about Edinburgh trams shall we?), and ideally find the fastest, and least taxing route to where I need to be.

The city is a place full of buildings. If it wasn’t it wouldn’t be a city. Some of those buildings are schools – and thus a city is also where I am educated – and some are stadiums, which are also places with their own special safety requirements. It’s a place that provides entertainment and hospitality, not just to its citizens but to city users.

The city is a place with finite resources which need to be used with effectiveness and efficiency.

But not one, sole person is in charge of all of the requirements of a city. Nor in charge of all the resources. And many different parties impose rules and regulations, on citizens and on those that supply their needs.

So, making cities smarter is quite a challenge.

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So, what does “Smart” really mean?

Well, here we go. My first venture into the world of blogging. (Do most blogs start like this?)

I was asked to cover Smarter Cities as an “Industry Segment” in IBM back in January, and when I’ve been able to snatch a few minutes or hours here and there I’ve been trying to get a handle on what Smarter Cities is as an agenda, and what a Smarter City might look like.

So far I’ve come to the conclusion that although “smart” is a goal to aim for, there will always be something else that can be done “smarter”, and that’s because technology should always get better and be more capable. So, getting smarter with what technology affords us today won’t be as smart as what we will be able to do next year.

Initially I though being smart just meant using resources in a more efficient, more sustainable way, whatever those resources are: people, money, man made materials, and so on. But now I think that’s the outcome of being smart. Being smart, to me, is more about the ways in which we determine how to use resources in a more efficient, more sustainable way.

So, where in the past we may have used spreadsheets with rows and rows, and columns and columns, of data to try to work out the status of a situation, we represent that data in a far more effective way using tools such as dashboarding and 3D visualisations on maps which bring that data to life. And, we don’t just analyse what’s happened: we can predict what will too. But a Smarter City is so much more than that.

So, having though about what “smart” means, I’ll add the “City” next time around. (Already as I type this I can see future posts discussing topics such as what do we use the data for, how do we capture that data, what else should we capture, is it just about data?)

Should you have a desire to read more, and the official messages from IBM you can take a look at

Don’t forget, these opinions are my own.

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