When we discussed the original idea with Jane Porter and Jeanette Alfano from Optivo, we had a few requirements:

• To make it an official WARP for housing, with support from the NCSC

• To ensure it was more than a talking shop, and that participants learn from one another

• To make it a space for all organisations in the sector, regardless of size

Getting the NCSC on board was critical and, thanks to the support of Helen P and Cub L, we managed to secure their presence and advice at our meetings. Getting organisations of all sizes involved was also essential, and fortunately, this was achieved early on. The requirement to ensure the group enables learning from one another was perhaps the most challenging – sharing best practice and intelligence requires trust amongst members, and that takes time to build. Also, cyber security is a complex topic which at times can be very technical.

Four years on, we have a group with high levels of trust where valuable intelligence is shared at every meeting and there are great learning opportunities for everyone involved. There’s one member of the team who has been driving this over the years: Bruce Thomson.

Bruce is one of those rare individuals who is technically proficient and able to express complex topics in a simple way. He is our ‘resident hacker’ and has taken the group through a hands-on journey covering everything from email security to wi-fi and QR code hacking and dark web monitoring.

When looking at email security, Bruce not only explained the importance of things like DMARC and DKIM, but also built a tool that monitored the email setup of forum members, then produced a league table where everyone would challenge each other to improve. Bruce personally helped members of the forum to configure their settings and was always available to troubleshoot issues and do additional research.

One of my favourite sessions was when Bruce demonstrated how to create a fake wireless network to steal credentials. This took place when meetings were in person, and Bruce arrived with a backpack full of cables and gear and proceeded to show us how someone can compromise a wireless network in a public place by creating an ‘evil twin’. Bruce extended this experiment and built a fully mobile set which he carried in a backpack and looked for vulnerable wireless networks around his neighbourhood. These examples show that cybersecurity is not something that is limited to work, but something that impacts our everyday lives. Bruce would always say: ‘Use your powers for good’, and I think the impact Bruce has had in the information security community in housing is proof that he has successfully followed his own advice.

Bruce has decided to reduce his working commitments and will leave our Information Security Forum from October. As someone who is prepared for all eventualities, Bruce has made sure we don’t come back and drag him out of retirement by recommending Campbell Murray to take over as our new friendly ethical hacker. Campbell has a wide experience in cyber security and works regularly with NCSC and across multiple sectors. I am very excited about Campbell’s contribution and continuing with the hands-on learning that members value so much.

As we move into our fifth year, I just wanted to thank Bruce for everything he has done for the cybersecurity community in housing. The legendary sessions will be fondly remembered, and we will continue using our powers for good.

In this blog, I’ll be discussing the lessons we can learn from the Log4j vulnerability and how your organisation can get assurances in managing risks and protect itself from a major cyber-attack like this by being part of Housemark’s Information Security Forum.

There is an XKCD cartoon that I really like, and it became quite true before Christmas:

I am talking about the vulnerability in the Log4j software which is probably unfair to describe as a project maintained by a random person in Nebraska but it’s certainly a key component of the modern digital infrastructure. This security incident was discovered and reported by an engineer of the Chinese e-commerce retailer Alibaba on the 9th of December and very quickly the realisation that this was a major threat spread like wildfire across the cybersecurity community.

As always, one of the first challenges was how to explain the issue to non-technical people. How to describe the threat and scale of the problem in simple words which could justify the resources needed over the next few weeks to fix or mitigate the issue. As always, Twitter produced the best answer:

There were some creative alternatives that point to the fact that you probably don’t know where this vulnerability may be located.

However humorous and creative these explanations are, the risk is very real with some experts defining this issue as the biggest security vulnerability in history and one that will haunt the internet for years. The National Cyber Security Centre (NCSC), produced clear and concise management explainers including one for board members and detailed technical guides.

The Log4j vulnerability is a perfect example of how difficult it is for organisations to achieve some level of assurance that they are managing the risk from cyberattacks. A lot has been written about the asymmetric nature of cybersecurity threats, and it is a recognised fact that most modern businesses with internet connectivity and presence are constantly under attack from a wide variety of motivated, creative, and adaptive adversaries that work together forming what can only be described as a supply chain of cyber-crime.

One of the key strategies to deal with such an environment is to share intelligence and to collaborate. This is what Housemark’s Information Security Forum have been doing since late 2018. Formed as the Warning Advice and Response Point (WARP), for the social housing sector in the UK and supported by the NCSC, the group has over 20 members ranging from large G15 organisations to specialist care providers and ALMOs.

Even though the Log4j incident ruined a lot of people’s run up to Christmas, members of Housemark’s Information Security Forum worked together to identify the attacks, warn each other of issues they were experiencing, and looked for potential solutions.

Over the last few years, members of the forum have been able to share invaluable intelligence on security incidents and threats, such as Log4j, but also on products and how to get the most out of them and most importantly, what works and what doesn’t when implementing security controls, rolling out awareness campaigns and communicating with senior leaders. The value of being able to learn from others, ask questions and access the wisdom of the crowd in a safe environment with high trust is something unique to this group.

With the level of trust built over the years, we can challenge ourselves and aim to improve together. An example of this is the work we have done on email security where we have created a league table of members and worked together to improve the standard of email security across the group. Very often, members of the group report that they’ve been given the green light to make a change or implement control in their organisation because the Forum recommended the approach and others in the group have done it successfully. I cannot think of a better way to spread best practice in an environment where working alone does not pay off.

The next time the execs in your organisation ask you about the latest security threat, don’t send them a clever tweet to explain it, tell them you discussed it at Housemark’s Information Security Forum and colleagues there recommended a series of actions which other organisations in the group have successfully tested and implemented. If you want to experience what it’s like to join a group of cyber security and data protection professionals in the sector, get in touch.

Perhaps the most painful incident for those of us who work with data was when around 16,000 positive cases were left out of the official daily figures because of an error in Excel. I followed the outrage online and shared the feeling of incredulity that such essential data analysis in time of crisis was being done using Excel. But at the same time, I wasn’t surprised. It is a well-known fact that Excel is the world’s most popular programming language. It allows domain experts work with data independently from IT. This is an opportunity and a risk as Public Health England painfully learned. 

Excel always divides opinion amongst data leaders. In housing, as in all other industries, the use of spreadsheets is widespread and gives analytics teams absolute nightmares. There are countless examples of Excel spreadsheets acting as the key data source for essential business processes. There are instances where spreadsheets are so complex that experienced developers are afraid to ‘touch’ them. But amongst all the hate, there’s a recognition that Excel helps users get closer to their data, that data is becoming fundamental for all jobs and that Excel is one of the gateways into data literacy. Excel is here to stay and finding a place for the humble spreadsheet amongst the myriad of analytics tools is one of the key decisions data leaders need to make.

One of these new analytical tools growing fast in the sector is Power BI. This tool was released by Microsoft to the general public in 2015 and has continued to gain momentum with every new release. Power BI evolved from within the Excel product, initially as a set of add-ins which gave users extra functionality and later as a standalone tool for advanced analytics. Users find the transition from Excel to Power BI much easier than with other tools. Once familiar with Power BI users can start working with visualisations to represent their business data and share their analysis across the organisation. The ability to represent quantitative information in accessible visualisations is a powerful skill which has the potential to surface new insights which were hidden in plain sight such as the famous case of John Snow’s map of cholera infection clusters in Soho in 1854.

Visualisations that help us understand complex data have been prevalent during the Covid-19 pandemic with notable examples from The Financial Times, The New York Times and Our World in Data. Scientific evidence backed by extensive data and presented in clear and engaging visualisations have helped governments make very difficult decisions and explain them to the public. These actions have literally saved lives and is an extreme example of how data informs decisions which ultimately drives action. This is what most organisations in the housing sector are grappling with. How to become more data data-driven, how to use the large amounts of data in their systems to inform the right decisions for the benefits of residents and colleagues. This Coronavirus crisis has only accelerated the urgency of this change.

So next time you are in front of Execs in your organisation ready to present the findings from your analysis which started as a concept in Excel and evolved into a sophisticated Power BI dashboard; remember the words of Professor Chris Witty on a cold Halloween night in 2020 and make sure you bring a clicker! 

PS Here are a few great visualisations I have selected. If you have any others you would like to share, please let us know and we can add them to this article!

Two years later, a global pandemic would provide a perfect and tragic example which will forever define what it means for an unexplainable algorithm to make a decision with a major impact on people's lives.

Everyone knows the story. The Coronavirus would force schools to shut down in March 2020 and a decision was made early by the government that A-levels and GCSE exams would not be taken, and an alternative method of awarding grades would be developed by Ofqual. A few months later, when the results came out and caused a significant number of students to have their expected grades downgraded, the inquest started immediately, and the culprit identified. It was an algorithm that had taken a number of rules, crunched them, and provided a result with massive real-world consequences for a whole generation of students. The fallout has been epic, and the knock-on effects will take years to unravel.

There are significant lessons for Housing organisations as the sector makes more use of data and algorithms to support decisions.

• Colleagues working with data should consider the impact of working with small cohorts which in the case of the exams algorithm ended up benefitting private schools over state schools with larger classes and a wider distribution of grades.

• Strategy and policy colleagues should think carefully about how implementing some policy objectives may have unintended consequences. In the case of the exams algorithm, the policy objective of Ofqual is to ensure exams are fair and even with year-on-year comparability regardless of any changes in curriculum or grades methodology. Having to implement this policy in a year in which exams were cancelled due to the pandemic triggered the creation of a set of complex rules which disregarded the assessment of teachers and ended up causing inexplicable and unfair results.

• Data models should be put through a ‘common sense’ test to challenge the results which don’t work in changing circumstances. In the case of the A-levels algorithm, the award of ‘U’ grades is a Good example.  In a normal exam year, ‘U’ grades are mostly awarded to students who don’t take the exam. This is frequently due to a misfortune such as a panic attack on the day, a bereavement or an accident. In 2020,  ‘U’ grades were distributed by the algorithm based on its defined rules but when you apply a ’common sense’ test to this, it looks pretty odd for an algorithm to statistically distribute unpredictable events. You cannot fail to turn up to a non-existent exam!

• Organisations should comply with a recognised data ethics framework in their advanced analytics projects.

• Leaders should be aware of the impact of algorithmic decision-making and try to work in the open when developing these approaches. Ofqual, to their credit, consulted heavily on their algorithm but still several mistakes were made which ended up contributing to the fiasco

 
The chair of Ofqual, Roger Taylor, said to the House of Commons Education Committee that it was a "fundamental mistake" to believe that it “would ever be acceptable” to use an algorithm to award grades for this year’s A-level. This is a serious blow to public confidence in algorithmic decision-making and particularly ironic coming from Taylor who also chairs the Centre for Data Ethics and Innovation which was created in those early days of GDPR to provide clarity and trust in algorithms.

The importance of data-based decisions, which has been highlighted during the pandemic, will continue to grow, but Housing colleagues must learn from this cautionary tale and ensure the necessary controls are in place and data can be trusted. Organisations will have to work harder than ever to regain trust as the mutant algorithm could strike again.

Aravena had already solved an urban challenge common in 3rd world countries like Chile. In 2004, his company won a government tender to create a housing project in the city of Iquique in the north of the country. A one-acre plot of land in the centre of the city had been illegally occupied by 100 families who had built temporary dwellings and were fighting any attempts by the government to relocate them to the periphery. The government tender was ultimately an impossible challenge as it required the winning bidder to resolve the following equation:

X = 100 families x 430 square feet x US$10,0001 acre of land

The government funding was capped at US$10K for each family which must include the cost of buying the land, providing the infrastructure and building the homes which must be of at least 430 square feet. Since the land was in the centre of the city, the cost of it was three times what social housing project in Chile could afford. Under any normal evaluation process, this tender could have only been resolved by moving the families to the periphery or building a tower block. 

Aravena’s winning bid did not propose a specific solution but a process of participatory design with the families which would involve them directly in solving the seemingly impossible equation. The process involved looking at the constraints and compromises needed. The only ‘viable’ option of building a tower block was quickly discarded when the families threatened to go on hunger strike. The reason was that the 430 square feet property size was not big enough for any growing family. What was the solution they designed together? 

Build half of a good house!

The solution used the government money for buying the land and building the components of the home which the residents couldn’t build, such as infrastructure, sewage, plumbing, etc. The design met the needs of the families by offering an expandable house in a high land value location.  Because the families were able to stay in the centre, they were able to participate in the wealth creation which happens in cities, maintain their natural networks and thus to start building ‘the other half’ of the house very soon after completion.

This example may seem literally miles away from the social housing issues in the UK but learning how participatory design is being used to solve third-world housing problems is even more valuable than learning from ‘best in class’ global enterprises.

Participatory design is equally applicable to our sector.  It can, for example, be applied when engaging in service co-creation with residents and empowering them to use their own resources to solve common problems. 

Applying the lessons of participatory design to digital transformation is about ensuring residents are co-creators of the services they will use online. This is not how most of the social housing sector goes about designing and developing digital services. As a result of current ‘top down’ digital design, online services are not always used by residents and sometimes have unintended consequences like an increase in the volume of calls or duplication of issues reported.

HouseMark has been working over the last three years to support our sector in digital transformation.  We have observed that something about the culture and operations of housing providers is preventing them from adopting the user-centred design approaches which are second nature to ‘best in class’ digital organisations.  This approach goes against a trend in the sector of finding innovative technology to drive digital transformation which follows the logic that a solution from a different business context can also solve housing problems. This may work sometimes, 

And it seems that the sector is also beginning to recognise the issue.

At the closing session of the 2019/2020 programme, we asked participants to share with us what they had learned from taking part. Most organisations said the same things:

• working through user-centred design methods had forced them to take a long look at their culture and question some deeply rooted beliefs about digital transformation and how it should be done 

• the critical change they needed to make was spending more time doing research with users to understand the problem and not jumping into solutions was the main insight

It’s all about learning to fall in love with the problem and not the solution. Following this principle will lead to closer working with residents and ultimately better digital solutions.

Probably the only way to ensure success going forward is to co-create solutions with users. The involvement of residents in the design of the solution weaves in the intention of all stakeholders into the service, building a shared narrative around it. Being able to design services with the right mix of human and machine elements will be a critical set of skills for transformation leaders going forward and the way to get this balance right is to get closer to the people using the service.

The lesson from the 100 families in the north of Chile who solved their impossible equation is that complex problems need radical solutions which can only be designed together with users.

This article was published in the fifth issue of the DIN Bulletin

As expected, social media opinions ranged from anger at how Uber benefits from people’s misery to acceptance that this is capitalism in action and Uber is just reflecting the real ‘value’ of a 10-minute journey evaluated by supply and demand and accelerated by algorithms designed to optimise their outcomes. 

I looked at this from a different perspective; to me this is a perfect example of the new challenges emerging from the practice of algorithmic management. I was curious to find out how the drivers would justify the price. Side with the passengers feeling ripped-off? Dive deep into the intricacies of surge pricing? Shrug their shoulders and blame the system?

“Algorithmic management is not an example of a technology-supported management practice; in fact, it constitutes a totally different managerial logic. Specifically, algorithmic management has the unique ability to track worker behaviour, constantly evaluate performance with rewards and penalties and automatically implement decisions. Algorithmic management provides the feeling of working with a “system” rather than humans and is characterised by lower transparency.1”

The feeling of being managed by some obscure, impregnable system has generated some interesting coping mechanisms by the growing number of people who work in these environments. I was fascinated by a report showing how a group of Uber and Lyft drivers working outside an airport in Washington would coordinate to switch off their apps to create an artificial absence of cars prompting the systems in both Uber and Lyft to trigger a price surge. An original way to regain control or just plain old cheating?

The impact of the gig economy on the workforce is not a new phenomenon, some social commentators have described a new emerging class of the ‘precariat’ which describes a growing socio-political group who share an increasingly precarious lack of job security. Algorithmic management has not created the precariat but is certainly defining the framework for managing this dispersed workforce.

Even though the most dramatic examples involve people working in the gig economy, the experience of being managed by an algorithm is becoming more common and is something which is manifesting itself in housing. Rent officers in many organisations regularly follow algorithm-based logic to decide who to call and chase for payment. Repairs operatives look at their devices to tell them which job to handle next and a transactional satisfaction survey is sent for customers to complete as soon as they leave. With the introduction of machine learning products embedded in Outlook which give users ‘nudges’ on how to become more productive, which emails need urgent action and suggestions to prevent spending too much time on meetings, this trend not only affects gig economy workers but is becoming more widespread and will continue to grow.

There is a fascinating study about the impact algorithmic management has on gig economy workers and I think it provides valuable insight for housing providers. The three most common complaints from workers managed by algorithms are:

• Constant surveillance - Staff feel the work is too prescriptive with every task decided by the algorithm and the threat of potential punishment for non-compliance. There’s also the personalised feedback loop from customers in the form of which adds to the feeling of lack of freedom

• Lack of transparency - As per the example of the price surge in London, staff feel they need to operate under the instructions of an opaque system which manipulates their activities towards goals which are totally out of their control

• Loneliness - Perhaps in common with home workers, staff feel isolated without colleagues to engage with or supervisors to build a relationship with.

All of this is triggering online activism with communities of gig economy workers sharing their experiences away from their employers. In some recent examples, fledgling trade unions are being formed to represent this growing workforce. Mark Graham, one of the key thinkers in the domain of the gig economy, has suggested the need for a transnational digital workers union.

Even if we don’t recognise all these traits in our workforce yet, we need to keep learning from the experience of other sectors and avoid some of the excesses described here. Practising openness and transparency, enabling human contact for dispersed teams, building trust around the goals of the organisation and ensuring that algorithms are optimising their output in line with the company’s goals, are all steps which will go a long way to preventing some of the unintended consequences of algorithmic management.

Keeping an eye on these new ways of managing people by algorithm is not only important from an HR perspective but it may have a deep impact in terms of customer satisfaction. The reason why the housing sector is looking to digital transformation and innovation is ultimately to improve the service it provides to its customers. The learning from the more extreme examples of the gig economy show us that a workforce which is experiencing unmitigated algorithmic management will be unable to provide an excellent customer service. This poses a significant challenge now when tenants expect more from landlords and are finding their voice to state their rightful demands to be listened.

At HouseMark we have been leading the collection of customer satisfaction data since 2011 when we launched the STAR framework. This year we have been carrying out a review of STAR to ensure we maintain a modern approach to capturing customer satisfaction data. We’ve had significant traction with over 250 landlords and over 7,000 residents participating in the review.

It is very interesting to see the prevalence of transactional satisfaction measures used in the sector. Landlords find these a highly effective way to manage third party contractors and define staff rewards. This is not in itself a problem but the lessons from the gig economy should help define a safe path where the combination of algorithmic management and the use of immediate feedback loops doesn’t cause unintended consequences such as low staff morale which will ultimately impact on satisfaction scores.

Another interesting insight from the review is the use of satisfaction measures which evaluate ease of use and trust. This is another area where landlords should monitor the impact of some of the algorithmic management challenges particularly when measuring trust. Some of the providers of mass-scale services supported by the gig economy workforce such as Uber or Amazon may accept a low trust score because they know customers will be willing to sacrifice trust for convenience. This is not the case in social housing where the product is the home and trust is a precious commodity. If staff feel they are managed by an impersonal system which they don’t understand, it is very unlikely they will be able to engender the kind of trust in customers needed to successfully deliver the service. 

When the new STAR framework is released in December 2019, the sector will have a new mechanism to capture satisfaction and providers will be able to ensure some of the inevitable changes brought about by technology and algorithmic management don’t create unintended consequences which impact their satisfaction scores due to low staff morale.

So the next time I get a nudge from Outlook telling me to respond to an email or to leave more time aside for collaboration, I will remember that for every fantastic new invention there is a potential unintended consequence and it is the job of the disruptive innovator to keep looking for them before they materialise and design strategies for safe adoption.

This article was published in the fourth issue of the DIN Bulletin

We know what happened; the goal was disallowed because the England player was offside according to VAR using the virtual offside line rule. Here’s an extract from the FIFA website explaining this technology:

‘Virtual offside lines are superimposed on the broadcast image by computer software.  Angle of view, lens distortion, field curvature and many other factors are considered when calculating the true position of these lines’.

There are a few interesting considerations from this single football incident, but to me the most fascinating one is the prevailing feeling that it was a fair decision. That even if we don’t like it, there is an objective way to determine the truth.

How did we get there? How can irrational fans accept that their wild celebrations were short-lived and ultimately pointless? There’s only one answer: Technology. Whereas in the past, referees would be turned into legends or hate figures because of their oversights or mistakes; today, thanks to technology, there is an objective truth created by the cold, impartial stare of computer vision and 3D modelling. 

It is interesting to compare how technology can provide the objective truth in one domain but obscure it in another one. We are all familiar with the post-truth world created by mass scale disinformation enabled by technology. The examples from Cambridge Analytica and the recent debate around the inaccuracy and bias of facial recognition techniques used by police forces in the UK demonstrate this trend. 

How do we benefit from the potential of disruptive technology without eroding the trust of our residents? This is one of the key questions for digital leaders in housing responsible for building an effective customer experience. We know that in housing, the trust between residents and landlords is weak and this has been emphasised by the Green Paper for Social Housing and its focus on consumer metrics aimed to provide a measurable improvement in customer experience. How does this work when the customer experience is shifting to digital and the most disruptive tools and approaches are suffering from a major public backlash (techlash)?

Some positive solutions to this challenge are emerging from the practice of design thinking which combines some of the skills and tools used by designers with a relentless focus on looking at issues from the perspective of the user. The UK government is a global centre of excellence in this discipline with a strong practice across departments, kicked off by GDS. The outcome of implementing these techniques in the development of digital solutions is a better customer experience because users have been involved from the start and services have been designed around their needs. This is essential to meet the demands of the green paper around resident involvement in the co-creation of services, but it is also good business sense as poorly designed digital services end up generating more back-office demand and decreasing customer satisfaction and trust. A growing number of organisations have already realised the key role that good user-centred digital service plays on building trust and have embedded it in their design manuals guiding all their activities. Here are some examples from the NHS, Coop and a template for charities

At HouseMark we are seeing a growing interest in design thinking approaches to digital services. Our digital transformation programme is focused on sharing skills and lessons from organisations inside and outside the sector who have transformed their customer experience. In partnership with BT, we take participants in the programme through an intensive 2-day hothouse at Adastral Park where design thinking and user centred design techniques are put to the test. We expect a significant improvement in digital services in housing over the next few years as the need to deliver true co-designed services with residents gains momentum through the green paper imperative and colleagues in the sector embed user centred design into everything they do.

One of the foundations for building truly user centred digital services is to carry out effective and regular user testing. How can you build a service from the perspective of the user if real people are not involved in testing them and providing feedback? User testing is not some vague one-off consultation effort but an embedded practice which must form part of every transformation team. High quality user testing comes with some important challenges which are being highlighted recently in the debate around dark patterns and efforts to legislate them in the US senate.  A dark pattern is a digital user interface which has been designed specifically to trick users into doing things. Examples of this type of design are everywhere on the internet, from the service that is easy to get into but almost impossible to escape; to the application where additional items are added to the shopping basket via imperceptible opt out options; to websites that ask for email or social media permissions for one purpose but then use the data to send spam emails. 

User testing will prove that a specific service meets the users’ needs and delivers a great customer experience, but it can also prove that the desired user behaviour can be engineered by using things like dark patterns. Someone’s design flair is someone else’s dark pattern. Digital leaders in housing must be aware of these emerging challenges and be vigilant not to appear in name and shame lists such as the #darkpatterns twitter hashtag. 

So, the next time you sit at a football ground wondering whether to celebrate or not while the person in black with the whistle waits for the decision of a computer to determine the truth of what really happened; don’t feel despondent. At least in that stadium there is trust in technology supporting the truth. When you go back to work on Monday building disruptive digital services you will be negotiating a rather more nuanced environment and wondering how to make sure tech is on your side of the offside line.

This article was published in the third edition of the DIN Bulletin

‘There were three working assumptions: first, the scientists and engineers understood that the new data systems would produce a brand-new knowledge domain. Second, it was assumed that the rights to that new knowledge and the power to use it to improve one's life would belong exclusively to the people who live in the house. Third, the team assumed that for all of its digital wizardry, the Aware Home would take its place as a modern incarnation of the ancient conventions that understand "home" as the private sanctuary of those who dwell within its walls.’

What I find fascinating about the Aware Home is how different reality turned out less than twenty years later. The technology that powered this futuristic experiment has now become mainstream, but the vast amounts of data collected by the plethora of IoT devices does not belong to the people who live in today’s version of the Aware Home. We seem to take for granted that these internet-enabled services will be collecting our personal data and sharing it widely; sometimes in unexpected ways such as when an Alexa device in the US got its voice commands mixed up and emailed a recording of a private conversation between a couple to one of their friends. Despite these extreme examples we continue buying these products, hoping this won’t happen to us and accepting the collection of our personal data in exchange for services. We have agreed to these terms and conditions. It’s just that we do it without thinking.

The legal framework of the internet is based on complex contracts that nobody reads. The Australian consumer advocacy group Choice hired an actor to read the 73,198 words of Amazon Kindle’s terms and conditions. It takes 9 hours! In a similar study, a group of researchers from the University of London determined that if a customer were to enter the Nest ecosystem of connected devices and apps they would need to review around 1000 contracts.

It is even argued that these contracts are carefully designed to nudge users to click without thinking, as an automated response to a carefully crafted stimulus. I find myself clicking ‘agree’ many times a day and consider it part and parcel of using the internet and technology products.

What is probably most ironic, is that with the introduction of GDPR in May last year there seems to have been an explosion in the number of agreements to click on every site. What is also true is the exponential increase in data breach complaints to European data protection regulators. Since the introduction of GDPR there have been over 95,000 complaints raised. This points to a growing dissatisfaction with the current state of affairs. Some of these complaints are being raised by UK social housing tenants or leaseholders who have an expectation that their landlords are protecting their data. This will become increasingly complex as the sector deploys IoT technology more extensively.

There is another interesting dimension to today’s reality which wasn’t envisaged in the year 2000 as part of the Aware Home’s experiments. As more intelligent devices are installed in the home and connected to the internet, the risk of an attack by hackers takes an entire new dimension. There is now the possibility to hijack internet-connected ‘things’ which interact with the physical world. All of a sudden the role of cybersecurity experts goes from preventing an attacker being able to encrypt someone’s spreadsheet or send phishing emails to trying to deal with attackers who are able to  stop someone’s pacemaker, take control of a crane in a construction site, replace the video image and sound from an internet connected doorbell device or simply hijack the home’s thermostat and ask for a ransom.

The security of the connected home is becoming a national defence priority for many countries as highlighted by the Japanese government’s effort to hack IoT devices in the homes of ordinary members of the public to identify weaknesses and resolve them in advance of the 2020 Olympics.

We have managed to turn an idealistic experiment from the year 2000 into everyday reality but at the same time introduced new challenges regarding the ownership and protection of the behavioural data collected as part of the use of internet-enabled services. We are also becoming aware of the potential for cyber attacks on the physical world which may cause problems at an unprecedented scale. One thing is sure; the drive to build the connected home of the future will continue and is something which the housing sector must embrace. 

What skills will the housing staff of the future need in order to advice and protect their residents? Will it be necessary to write alternative user guides such as these which focus on how to be aware of and minimise the inevitable digital surveillance being introduced into their homes with every new IoT device? Will it be necessary to have the skills to prevent attacks into internet connected home equipment or the building management system? In relation to the complex and extensive contracts, will landlords be able to provide clarity for residents to understand what happens to their data?

At HouseMark we have been thinking about these issues for a long time and in 2017 published ‘Transparency and Trust: A guide to data protection and privacy for social landlords and tenants’ which provides extensive guidance on how to safely collect, use and store personal data in the housing sector. Following the significant interest generated from this publication and to dive deeper into these issues we have established a Warning Advice and Response Point (WARP) for housing providers. WARPs have been going in the UK government for over 20 years and are groups of cybersecurity and data protection experts who work together to improve the security of their organisations through information sharing and collaboration. Chaired by Jeanette Alfano, Director of Technology and Transformation at Optivo and managed by HouseMark; the group started meeting in 2019 and collaborating on key topics such as the challenges of secure communications with partners such as local authorities or the police, how to mitigate security risks by achieving Cyber Essentials Plus certification and more immediate concerns such as how to respond to the letter from Fiona MacGregor to all CEOs of housing associations regarding the access to data stored in cloud facilities in Europe in the scenario of a no-deal Brexit. 

We are aiming to keep the current group small with no more than 25 organisations but we are hoping to grow into regional WARPs over the next 6 to 12 months. With support from the National Cyber Security Centre and a number of security experts, we will be building the resilience of the sector to ensure that as we move to a more connected future with all its challenges, we have the tools and the skills to respond. If you are keen to join, please get in touch.

This article was published in the second edition of the DIN Bulletin

For those of you not as fanatical about the movie, a bit of context. Five astronauts are sent on a mission to Jupiter to follow signals discovered on the moon in 2001 emitting from a black monolith towards Jupiter’s moons. The spaceship is completely controlled by HAL 9000, an intelligent computer which has never had a fault. In the scene depicted above, the astronauts lock themselves in a capsule to discuss HAL’s behaviour (which at this point has become rogue) and their options for disconnecting it. They believe they are safe as HAL cannot hear them…

As I was leaving the cinema, I couldn’t stop thinking about how well a movie in 1968 represents the fear, uncertainty and doubt we feel about Artificial Intelligence (AI) and Machine Learning fifty years later. With depressing news every day about machines taking over people’s jobs, it’s no surprise we feel like staff at the supermarket self-checkout assisting shoppers with the automated machines as we accelerate our own path to unemployment. Feels like the design of a cruel Greek deity but it’s just disruptive innovation at work. The same it has been through history.

Artificial Intelligence has had a lot of bad press so perhaps starting with a definition is necessary. 

AI is the designing and building of intelligent agents that receive precepts from the environment and take actions that affect that environment. 

This definition from Russell and Norvig is considered the gold standard as it covers a large spectrum of activity ranging from computer vision, speech processing, natural language understanding all the way to robotics. Based on this definition, I don’t see the inevitable link with machines taking over control of the world but as technology continues to improve at its current pace, more activities which used to be done by humans are taken over by machines. Let’s use a recent example:

This year in Wimbledon, all the highlights packages were automatically produced using IBM AI technology to analyse the video, determine the best plays, edit the content and finalise it ready for sharing online or providing it to media organisations. The highlights process was reduced from 3-4 hours to a few minutes allowing the Wimbledon media team to focus on higher-value engagement activities.

The fact that Wimbledon media staff can focus on activities which generate more engagement is key in this example as it illustrates the subtle difference between world domination by evil technology and what I think is really happening. Let’s look at another example which makes this even more evident:

In August this year, Deepmind in collaboration with Moorfields Eye Hospital developed an AI-enhanced process to detect eye disease which ‘can correctly recommend how patients should be referred for treatment for over 50 sight-threatening eye diseases as accurately as world-leading expert doctors.’ The challenge being tackled here is related to the amount of complex 3-D images doctors need to review (1,000 / day in Moorfields Eye Hospital) and the level of expertise required from doctors to interpret these images. Since delays in treatment can cause patients to lose their sight, any improvement in the speed of eye disease detection can have a major impact.

The two examples above can be interpreted as proof that machines will be doing the job of doctors and TV producers, but we need to look at this differently: AI augmenting human intelligence. This view challenges the pessimism and fatalism with which AI is being looked at today and a few thinkers in this space are not using the term AI anymore but flipping it to IA which stands for Intelligence Augmentation. Under this interpretation, the potential of the technology becomes clearer and practical solutions become more realistic and achievable as machines don’t need to compete with humans but work together. Every time an article talks about the demise of a current job because of AI, it is important to focus on which part of the job is being augmented by technology and what opportunity this creates.

To truly appreciate the power of Intelligence Augmentation, it is worth talking about Fan Hui, a 3-time European Go champion. 

Go is an ancient board game of strategy that has frustrated computer scientists and researchers for years. In Go there are more moves possible than there are atoms in the universe, so it has always been considered the greatest test for artificial intelligence. Fan Hui was selected by the London-based AI research company DeepMind (now owned by Google) to train the computer system which ultimately went on to beat the world champion Lee Sedol over 5 games. The training was done by Fan Hui playing against the computer and allowing it to learn and evolve its own strategies. After a few months, the machine started beating Fan Hui regularly and the team developing the programme decided that it would be more effective for the system to play against itself rather than continue playing Fan Hui. This should be utterly depressing but what happened when Fan Hui went back to play against other humans is absolutely amazing. Thanks to the interaction with the AI system his skills had improved significantly rocketing him up the rankings from 600 to 300 in three months.

We’ve applied some of this thinking to a new project where HouseMark is partnering with Lewisham Homes and Field Dynamics to look at how these modern data techniques can be applied to the specific problems in Housing and more specifically, to those of asset management. We have used 7 years of repairs data from Lewisham Homes to try and predict the repair costs for properties in the portfolio. This does not aim to remove the need for experienced asset managers, but these modern techniques can help Housing organisations manage their major work programmes based on predictive spend and allow them to regularly reallocate which properties should be in or out of the programme. This is another tool which augments the intelligence of the organisation and gives a new perspective to base decisions on. It is early days, but the initial results are very encouraging. We are looking to get a group of organisations to work together in a collaborative project to build this system as a product which can be used across the sector. We are particularly interested in working with asset management practitioners to understand how these techniques will augment their skills and potentially transform their jobs going forward.

If artificial intelligence viewed as intelligence augmentation can transform the work of doctors, free up TV producers and exponentially improve the skills of a Go player. What can it do for those of us who work in Housing? The answers will not come from raging against the (learning) machine.

This article was published in the first issue of the DIN Bulletin