Breaking the Mould

The Institute for Safe Autonomy and the School for Business and Society at the University of York are leading a pilot study into the use of internal environment monitoring systems that could help with the detection of damp and mould in homes. Led by Philip Garnett, a professor in the School for Business and Society and Ethics Pillar Lead in the Institute for Safe Autonomy, and in collaboration with North Star Housing Group, AwareTag, and Waterstons. We will be placing sensors into social housing for the purpose of monitoring temperature and humidity levels with the aim of detecting conditions that might result in damp and the growth of mould, conditions that might eventually pose a risk to the tenant’s health. The project will run throughout 2024, and is focused on engagement with social housing tenants around the use of autonomous sensor systems in homes for the use in this sort of predictive analytics.

There has been a lot of interest in the issue of damp and mould in housing due to a number of tragic incidents over recent years, including the death of a two-year old Rochdale boy in late 2020. Due to this and other similar incidents there has been increased scrutiny of damp and mould in social housing by the Government, regulators and the Ombudsman, including the Government proposing changes to the Social Housing (Regulation) Act. The result of this will be more regulatory oversight of the management of damp and mould in homes. To assist with the monitoring of housing some social housing landlords are deploying internet of things technology (IoT), and other AI or machine learning driven technologies, in the form of temperature, humidity, and sometimes carbon dioxide sensors, with the hope that such technology can detect issues before it becomes a serious problem, and allow the landlord to act accordingly.

Rather than to focus on the efficacy of the technology alone, the purpose of this pilot study is to engage directly with the tenants of social housing to understand how they feel about the deployment of such sensors in their homes. With North Star Housing Group we will be conducting focus groups with groups of tenants to discuss the use of sensors broadly, enabling an open discussion about the positive and negative aspects of their use. AwareTag will also be supporting the deployment of sensors in a small number of homes to research their use in practice, and get feedback on the technology from tenants. Waterstons are also providing advice on how the technology can be secured and the privacy of tenants protected. The views of the tenants are central to this issue, and their opinion on whether a technological solution is in fact a valid solution to this issue, and if it is how that technology should be used and deployed. It is expected that this pilot study will lead to future research projects at a larger scale.

“We are very excited to be working on this project, as it allows us to work with our customers to understand a landlords role in IoT devices and the data they produce. We are always looking for ways to innovative to provide an enhanced customer experience and offer but this work ensures we are doing so, consciously and keeping our customers involved”.

Sean Lawless – North Star Housing Group

This is a reposting of a blog posted on the Institute for Safe Autonmy’s LinkedIn page.

Supply Chains Need Protection from Covid-19

Covid-19 coronavirus is bound to have significant impact on global supply chains as it impacts all sectors of the economy. See graphs from the Spectator for illustration. It is also somewhat unprecedented as it in many area both supply and demand are impacted. Both our ability to consume and produce has in many areas been significantly impacted by many countries adopting long periods of lock-down. Covid-19 is therefore a systemic shock to the economy, and a systemic shock to supply chains.

Systemic Impact on Supply Chains

The danger with supply chains is that Covid-19 significantly disrupts what are now frequently called supply chain networks. Where the term network recognises the complex inbound and outbound interdependencies between organisations. Supply chain networks are difficult to fully map and understand. Couple to this a move in the economy post WWII towards lean supply chains. Where there are low levels of redundancy in the supply chain, and resources (in all senses of the word) are delivered just in time. Disruption in one part of the network can quickly spread (cascade) to other areas. This could cause the network to fail in unpredictable ways. Where the ability of an organisation to produce something being halted by it being unable to acquire an essential input. Materials, parts, service, resources in general.

Supply Chain Deadlock

The danger with a large scale systemic shocks is that they sufficiently disrupt something like a supply chains to the point where it can no longer function. In the case of supply chains and Covid-19, one possibility is that they become deadlocked. The term deadlock is perhaps most frequently used to describe a situation where a series of interdependent processes all stop because they are all waiting for each other to do something. Process A is waiting for process B, B is waiting for process C, and C is waiting for process A. A situation that computer programmers have long had to deal with an mitigate.

Resource deadlock between two processes that are waiting for each other.
Resource Deadlock

This situation of deadlock could arise in lean supply chains. The operations of one organisation may be halted due to it being unable to acquire some essential resource for its operations. The halting of this organisation’s operations could have effects elsewhere in the supply chain. The difficulty is that this might not be a simple, easily mapped, supply chain. Similar to that shown above. Instead it might be a complex network of interdependent relationships, and therefore understanding how to release the deadlock might be extremely difficult.

International Coordination

If Covid-19 causes deadlock, releasing this deadlock in global supply chains will require international coordination. For example, it might require organisations to temporarily produce resources that they normally wouldn’t. Or resources might have to be moved between organisations. Both to allow processes in other organisations to get underway. There will need to be some way to both map resource requirements, and move them. This will need to be done internationally. Perhaps through the production of an international register of needs are resources.

Why The UK Covid-19 Strategy is High Risk

Thursday (12th March 2020) afternoon’s post COBRA press conference with the Prime Minister Johnson provided an interesting update on the UK’s strategy to delay the spread of the Covid-19 coronavirus. It was interesting because it diverts significantly with what many other countries are doing to limit coronavirus spread, but in my opinion is also a very high risk strategy.

Competing Strategies

The strategy seems to be largely based on getting people to remain at home if they think there is even a relatively small chance that they have contracted the virus (UK Gov Stay at Home Guidance). Thus, if you believe you might be showing symptoms of illness, isolate yourself for the period of 7 days. To facilitate this we are to ask our “employer, friends and family to help you get the things you need to stay at home”, sleep alone when at home, wash our hands and stay away from vulnerable people. Only if symptoms persist beyond 7 days or worsen are we to seek the advice of NHS 111.

Essentially this is a request from the Government that we act to remove ourselves from the circulating population at the first sign of illness. Doing this will ‘flatten the curve’, reducing the peak number of cases at any one time, and also push that peak into the summer months. At which point the NHS will be better able to cope. Sounds great if it works, but will it?

This strategy is in rather stark contrast to a number of other countries that have imposed highly disruptive restrictions to people’s movement and behaviour. Such as Norway (and Ireland) that advises against gatherings and human contact (NIPH), and has essentially closed itself off (Visit Norway). Italy, currently the worst affected country in Europe, has also imposed tight restrictions even on things like movement and shopping (BBC News). 

Its Complex

As a complex systems theorist this difference in intervention strategies is interesting. Complexity theory takes a view of the world as a system of interacting parts. It is also a relational worldview, which means it is not only the parts (such as people, buildings, objects general) that are important. The relationships between the parts, how they interact, is also important to how a system behaves. It is a systemic view.

The UK strategy seems to have at its centre the idea that a relatively small intervention in our behaviour, our relationship with each other and the world around us, will produce a significant effect on the spread of the virus. Self isolating at the first sign of illness, hand washing and so on. These changes are intended to flatten the curve of infection, lowering its peak, and move it to summer. This small intervention might be followed later by something more like what we have seen in Norway and Italy. The problem is, will such a small intervention limit the spread of pandemic flu?

Three Assumptions

There are at least three significant assumptions underpinning this strategy. On which its success depends.

One, people are willing and able to do it. They are assuming that people will do what they ask, and can do what they ask. There could be many reasons why people do not follow the advice. They might think that their symptoms have nothing to do with Covid-19, or don’t immediately recognise them as illness. Financially taking time off work might be impossible. Not all households have enough space at home to self isolate, including ‘sleeping alone’. Lack of compliance with the changes to behaviour will mean the virus spreads more quickly and they fail in their attempt to flatten the curve and shift the peak to the summer.

Two, they will know when to switch strategy. Central to the UK strategy is an ability to know if or when there is a need to switch from this modest intervention to a more draconian one. As at some point it is likely that more restrictions will be needed. When you do that is a trade off between wanting to shift that peak to the summer, and also limiting the spread. Also in the press conference was a decision to stop testing outside of hospital. By doing this they lose good data of how the virus is spreading in the population, making it harder to know when to change strategy. Perhaps making it harder to know when the system is approaching a tipping point into uncontrolled spreading.

There are hints that some of that data and analysis might be sought from big tech companes, with Buzzfeed reporting that Dominic Cummings will chair a “Tech CEO Round Table”. With the suggestion being that they have data that could help understand and combat the flow of coronavirus. This again is risky, as a source of data to understand viral spread social media is unproven, and perhaps this isn’t the time to be testing unproven methodologies. It does seem to betray some of the thinking within No. 10. That all problems can be manipluated through data and analytics, mediated via social media companies.

Three, changing behaviours will have the effect they predict. This assumption is more difficult to analyse and impacts any strategy. When we make changes to a complex system, in this case our day to day modes of interacting, working, and living. We cannot be sure that the system will react as we predict. It could quite easily do something unexpected, and that unexpected behaviour will interact with how the virus spreads. What that will do is currently anyone’s guess, but will soon be our lived experience. However it is an area of scientific study that we should focus more attention on. What are the systemic impacts of large scale interventions in societies? The types of interventions that will be needed to fight things like pandemics and climate change.

Is It a Good Strategy?

The logic of the strategy of countries like Norway is more simple that of the UK. There the idea is to be very restrictive and try to slow it down straight away. One would assume that they have factored in that it will not be fully complied with, some non-compliance with the restrictions will cause spreading of the virus. They might even be counting on that to spread it slowly to allow people to become immune without their systems being overwhelmed. This a shock to the system that they hope will flatten the curve.

The UK on the other hand is betting on compliance with their strategy, they need people to comply for it to spread slowly, flatten the curve, and move the peak. They are also assuming that they can spot the time when they need to move to Norway strategy should they need to. Both of these are more risky, in the sense that you are reliant on getting more things right. If people don’t comply the virus will spread rapidly through the population, and if they miss the time to change strategy then again it could get out of control.

Of course, if it works it will turn out to have been the right thing to do! However it is definitely very high risk, and the costs if it fails will be significant.

Ngrams – Computational Analysis of Google Ngrams Data

I recently did an invited talk for the student linguistics group at York St John University in York. The paper was broadly on the analysis of Ngrams data and was therefore a something of a summary of about 5 papers that I have been involved with over a number of years. It was nice to do a sort of overview of a fairly long project, and I was able to give the students a sense of how a program of research evolves as you get further into the empirical evidence and have to construct and test theories about what it is that you think is going on.

The work is an analysis of Google Ngrams data, where we attempt to explain the observed changes in word frequencies. Including the links between events and the words that we use in our language. We also investigated the explanatory power of the neutral model, and how well it fits changing patterns of word frequencies. I have linked the slides below so you can see what was presented, and the references are below that show the evolution of the work. I think I will do a podcast of this work in the future as I think its an interesting story.

Chip – the Algorithmic Savings App

I came across an App, while aimlessly surfing, it’s an algorithmic savings plan. I think that is the best way to describe it, or at least its a way to describe it. The point of Chip is that when you sign up you get a savings account, held by Barclays Bank PLC, and the app figures out how much money you could save (and not miss), and when. So every now and then Chip determines, via the magic of algorithms, an amount of money that you could save and not miss too much.

On the default savings rate it seems to be similar to the cost of a large latte and a chocolate bar. Chip then congratulates you your saving, you can back out if money is short. If you leave it to its own devices that sum of money disappears from your nominated current account to reappears in your new savings account.

Am I Using it?

Yes, I have signed up for the app. I thought that in general this isn’t a bad way to save. I have standing orders for saving a modest sum of money every month but I always thought I could do a little more. What Chip does is allow that to happen in a flexible way, no need to commit to a particular amount at the start of each month, and no need need to remember into get on internet banking to do it manually. Chip does it for you, and if you are a bit short one month you can stop the transfer. Great if your income is irregular and saving a fixed sum might be tricky.

Similarly, should you suddenly find you need money, you can easily get at the funds out of the savings account. This in my mind this makes this a sort of slush fund. Which you can dip into should need to, or are tempted to. I still think longer term savings are also a good idea. Putting a little away somewhere harder to get at, and also make sure you have a pension as soon as you can!

Saving Made Entertaining?

Chip makes saving about as entertaining as it probably could be. You get congratulatory memes when you save, and Chip is well chipper, and encourages you along your savings journey. The chipperness might drive some users slightly mad, but I think they got the balance about right. It does seem to work, or at least it does for me, after 103 days using the app I have saved slightly over £200. Which, although not a massive sum, is £200 more than I otherwise would have. I set a goal, rather arbitrarily, of £1500. Weirdly Chip seems to report that I am always about 95 weeks away from my goal… but whatever, I can see the amount saved go up and the amount left go down. Thats progress.

What About My Data?

In order to do all this Chip needs read-only access to your bank account. Now that is not data that should be handed over lightly. Sure your bank knows it, but your day to day transactions is very personal data. It provides a lot of information about how and where you spend you money, and thus who you are in a way. Chip is regulated by the ICO and they encrypt the data.

Chip has a data control licence – you’ll find us on the ICO register – and we always act in full compliance with the Data Protection Act. Your online banking login details are protected using 256-bit encryption and Chip does not store your data.

Chip FAQ

This was the part of the process that made me wince a little. However, if they are going to calculate a savings rate then they need (at least some of) this information. So, if you want in, this is the price you pay. I wanted to have a more detailed look at what and how they use my data. So I asked them a few questions, but they are yet to reply…

Images for Academic Work

I am always searching for places to get images that I can use in my academic work, teaching slides, presentations etc. To help me, and perhaps others, I have made a list of sources.