Inma Martinez, author of new book The Future of the Automotive Industry, on self-driving and connected cars

Street smart cars of the future will drive like a local and diagnose Alzheimer’s

Described by Time magazine as “One of the best talents in human digital behaviour”, Inma Martinez advises business leaders and governments (including the UK’s Department of Culture, Media and Sport) on AI and digitisation. She’s just written a book called The Future of the Automotive Industry, so obviously we had to ask her about driverless cars.

How did you come to specialise in automotive?

IM: “I first got involved in the auto industry in the early 2000s, when BMW recognised that they had to attract female drivers and buyers. We made a series of short films with directors including Ridley Scott and John Woo, starring Clive Owen as The Driver. Guy Ritchie’s had Madonna in it. In those days, I was working as a human factors scientist, looking at how humans use technology.

“Previously, I had been a telecoms engineer specialising in internet protocols. Then, because Nokia bought two of my start-ups, I landed in their innovations department. Together with Intel, we came to the realisation that telecommunications companies had to create alliances with auto manufacturers for vehicle to everything (V2X) and vehicle to infrastructure (V2I) communications.

“I worked for Volkswagen Group designing cars with AI and met Mark Gallagher and all the Formula One crowd. I thought: I have to write about the future of this industry, because in the next five to ten years it will not look anything like today – the massive influence of the Internet of Things (IoT) and AI, sustainability and the green economy. I wrote the book during the pandemic and it came out in June.”

Setting EVs aside, how do you view the autonomous side of things?

IM: “I love the topic, firstly because it needs so much definition. People interchange ‘autonomous’ with ‘self-driving’, but they’re separate things. Unfortunately, the media is not very sophisticated in talking about that.

“For me, it’s something that’s been happening for 15 or 20 years, initially because the industry was pressed to improve safety. You got level one autonomous features, like cruise control and parking assistance, making things easier and safer. Now we’re at level three, and no one understands what on earth is going on!

“I hate it when Tesla put out press releases claiming full self-driving. The PR houses are doing a disservice to the industry because they’re confusing people. I delved into this for the book and came up to the conclusion that we’re not going to see autonomous cars until the regulation is ready for them.

“The European Union put out a good first attempt to define self-driving in 2019, and Japan has changed a lot of its traffic laws to allow Honda to start putting level three cars on the road.

“This will only happen when the legal framework is defined. Otherwise, you have the massive legal issue of who’s at fault in a crash. There’s got to be an effort in the industry to help create these legal frameworks, and I don’t think it’s too complicated.

“The way I see it, we need to differentiate an autonomous car – a level five car which can do literally everything by itself – from self-driving cars which can drive and brake and accelerate and have situational awareness, but which can’t operate constantly by themselves and still need the driver to keep their eyes on the road.”

Proposed changes to the Highway Code talk of drivers not having to pay attention anymore. Is there a danger that regulators could jump the gun?

IM: “That is frightening. You can’t put vehicles on the road driving themselves with just computer vision, you need V2X, roadside units (RSUs), Vehicular Ad Hoc Networks (VANETs) – all the beacons that make roads smart. You need 5G infrastructure, so the car is actually guided by connectedness. This has to do with urban planning and smart cities, not with the automotive industry per se.

“The point is not just whether can we make cars autonomous, it is whether we can make them street smart. The way people drive is different in every country. In Rome, people brake all the time. In Kuala Lumpur, there are mopeds everywhere. So, the car of the future is going to have to be adaptive – the AI, computer vision, all the settings will be different depending on where it is.

“There’s a wonderful thesis that asks whether people are born street smart or whether they get it when they move to a big city. I began to think about autonomous cars driving around big urban centres – they’re going to have to get the pulse of how you drive in a certain city. We need to train the system to learn how to integrate itself.

“We’ve only just begun to consider what autonomous is, and we need to have a bold vision as to what it should be. In my view, we need to make cars smart, not just autonomous.”

What are the main risks in the shift to self-driving?

IM: “We need a legal framework. We need integration into the smart city infrastructure, including telecommunications. We also need definitions.

“Cars look fabulous at the Geneva Motor Show, but nobody talks about them in contexts. Should there be designated lanes for hands-free driving? How are we going to deal with a car parc that is not all digital, that still has a lot of older vehicles?

“Automotive is one of the hardest industries to create innovation because you have the pressure of safety, safety, safety at all costs. For example, nobody’s working on voice commands anymore because it turned out they were a distraction, a nuisance.”

Can you address the challenges specific to the UK?

IM: “Yes – your road network. In the UK you have a lot of 60mph rural roads where you can barely see what’s coming. I drive in Somerset and holy cow! It’s only because humans drive in such a super intuitive way that there aren’t more crashes.

“Perhaps it’s also because your driving test is so rigorous. I did my test at school in a small town in Pennsylvania. The police would make you drive around the car park and give you your licence. That was it.

“Then you have London, which is like no other city. It is a Dickensian city with 21st century vehicles running through it. It is a costly challenge to test smart road infrastructure without creating congestion. Where are the budgets going to come from?”

Anything else you’d like to mention?

IM: “I was speaking to a board member at Volkswagen recently and he said that one of the revelations of the pandemic was that it motivated people to own a car, rather than use public transport, for health and safety reasons, and a certain level of freedom and privacy. People have conversations when driving that they wouldn’t have on a train.

“It is also worth highlighting the prospect of the automotive industry partnering with healthcare companies on predictive medicine – keeping track of your vital biometrics to help detect serious diseases. If you’re going to be sitting in this highly technical environment for two hours a day, data such as the way you check your mirrors can reveal early symptoms of things like Alzheimer’s.

“Connected cars will add another layer of personal profiling and data authentication. Digital fingerprinting companies will be able to see that it’s me on my usual route, doing what I normally do. The cybersecurity will have to be very strong though. Imagine somebody hacking into the traffic management system of a future city – that’d be the ultimate hack.”

And on that very Italian Job note, our time is up. Inma Martinez’s book The Future of the Automotive Industry is out now, or visit inmamartinez.io

AI and IoT expert Karim Jaser presents a resolute defence of the trolley problem.

Ethics in self-driving: The trolley problem strikes back

The trolley problem – the question of who to save, or kill, in no-win crash situations – continues to divide opinion like no other subject in the driverless world.

I must admit to flip-flopping on it myself. From being quite taken with it in 2018’s Autonomous now: the shift to self-driving, through 2019’s The driverless dilemma: touchstone or red herring?, to last month’s Self-driving experts across the world agree: the trolley problem is a nonsense.

That, I thought, was conclusion reached, the end of the matter. Far from it! In response to the latter article, Karim Jaser, Senior Product Manager specialising in artificial intelligence (AI) and internet of things (IoT) for blue chip companies, posted a resolute defence of the much-maligned thought experiment on our LinkedIn page.

“I do agree that humans don’t go through the trolley problem evaluation in the split decision second, however I also think not all experts agree it is a nonsense,” he said. “It is for society as a whole to discuss these ethical problems. From the point of view of self-driving technology, this can be solved in many ways, with probability theory and estimations on minimal loss, but it is not up to developers or self-driving experts alone to decide how to tackle the point. It needs the involvement of regulators, governments and the industry.”

Karim Jaser
Karim Jaser, Senior Product Manager specialising in AI and IoT.

Well, with our mission to encourage debate about all aspects of autonomous vehicles, how could we resist? We asked Karim if he’d be up for an interview. He kindly agreed and here we present his thoughtful and cohesive opinion.

KJ: “I was always fascinated by robot intelligence, so at university I studied telecommunication engineering. There were lots of exams on probability theory, system control, software engineering. I was also involved in coding in my spare time, and later did it as a job.

“Self-driving is a control problem first and foremost. There are elements of robotics, including perception state estimation and trajectory planning, but also software, hardware and AI working together.

“The interest grew stronger when I started studying machine learning and AI about four years ago. When I was at university in the 90s, AI was not really a popular subject. It was a topic I picked up later in my career. As a senior product manager at a high technology company, AI is everywhere now – it’s an essential part of the skills necessary to perform and innovate, from biometric scans and image recognition to automated travel.

“AI has a lot of potential to have a beneficial impact on society – fewer accidents, better mobility, less pollution, more autonomy for people with disabilities – but it doesn’t come without challenges, for example, cyber threats, and also ethical and regulatory issues, which is why I got involved on the trolley problem.”

“It’s not straightforward. If we take a step back, you we need to understand how self-driving cars take decisions. They’re using supervised learning, reinforcement learning, convolutional neural networks (CNN) and recurrent neural networks (RNN), deep learning for computer vision and prediction. Specifically, reinforcement and inverse reinforcement learning are very tightly linked to the way driverless vehicles behave through means of policies.

“Policies are related to the distribution of probabilities, but the trolley problem is an ethical choice, so I understand why a lot of people in the industry dismiss it. It’s not the way autonomous vehicles take decisions, going through philosophical considerations in a split second, so it might seem irrelevant, right? Like the Turing Test and Asimov’s Robot Rules, the trolley problem can be perceived as a distraction from more practical considerations.

“It can be distracting for two reasons: first, these considerations are corner cases – there are other priorities, more likely scenarios still to be addressed; second, autonomous vehicles will not be given ethical guidelines to link with probabilities.

“With regards to the first objection, as Patrick Lin (director of the Ethics and Emerging Sciences Group at California Polytechnic State University) has pointed out, it shouldn’t matter if these scenarios are impossible, because the job of these thought experiments is to force us to think more carefully about ethical priorities, not to simulate the realities.

“The second objection is related to self-driving cars taking decisions through distribution of probabilities. The actions of these vehicles are linked not to hard coding, but all statistical contextual information, and that makes each scenario difficult to interpret. You can potentially have millions of mini trolley problems in different contexts.

“The trolley problem is a reminder that corner cases and autonomous vehicle behaviours are not a technical irrelevance. This is an issue that belongs to society and should be discussed in the same way as other AI pitfalls like privacy and bias.

“Actually, the trolley problem is more related to the third pitfall of AI, replicability. When trying to understand why and how an autonomous vehicle takes a decision, it is important to note that most autonomous vehicle developers are taking ethical considerations into account.

“In 2017 in America, Apple commended the National Highway Traffic Safety Administration (NHTSA) for including ethical considerations in its Federal Automated Vehicles Policy. It even highlighted three particular areas: 1) the implications of algorithmic decisions for the safety, mobility and legality of automated vehicles and their occupants; 2) the challenge of ensuring privacy and security in the design of automated vehicles; and 3) the impact of automated vehicles on the public good, including their consequences for employment and public spaces.

“The automotive industry has also approached the issue of accidents caused by autonomous vehicles in relation to ethics. For example, Volvo stated in 2015 that it would take responsibility for all Volvo self-driving car accidents. This is an ethical decision, because it did so without regulation forcing it to do so.

“We will see what happens. If there are no ethical decisions by the industry, the regulators will step in. On a fun note, looking to the past, horses were not considered responsible for their actions, the rider was. Whereas in this case, responsibility for the autonomous vehicle will lie not with the owner but with the carmaker.

“So, to conclude, automakers and AV developers are taking ethical and regulatory matters into account, which underlines the importance of these discussions. We cannot just dismiss the trolley problem because it’s not the way an autonomous vehicle decides, or because it distracts from technical development.

“The way to deal with this is to discuss the implications in the right context, being aware of how autonomous vehicles are developed without scaring the public with sensationalist articles. The trolley problem might be perceived as a Terminator-style situation, and that’s where it gets on the nerves of a lot of people that are developing and testing AI. It’s not black and white, it’s a grey area, and that takes us to the path of discussions.

“The trolley problem forces us to consider ethics in vehicle development and confront the fact that ethical principles differ around the world, as documented by the Massachusetts Institute of Technology (MIT) simulation.

“Are we at the point where discussing the trolley problem should be a priority? I believe that would be beneficial to the success of the self-driving industry, guiding us in the thinking process of building the right mix of safeguards and transparency.”

The UK’s National Physical Laboratory is working on a framework for virtual sensor testing.

Developing test frameworks which build a bridge of trust to driverless cars in the UK

Our Zenzic CAM Creator series continues with Andre Burgess, digital sector strategy leader at the National Physical Laboratory (NPL).

NPL is the UK’s National Metrology Institute, responsible for developing and maintaining the national primary measurement standards. For over a century, it has worked to translate scientific expertise into economic prosperity, skilled employment and improved quality of life, covering everything from cancer treatments to quantum computing. In the self-driving sector, Andre Burgess’s focus is test frameworks to support the deployment of safe and reliable autonomous transport on land, sea and air.

Andre Burgess, digital sector strategy leader at NPL
Andre Burgess, digital sector strategy leader at NPL.

AB: “We’re all about measurement and how it can be applied to the autonomous vehicle space. Artificial intelligence (AI) and machine learning represents a great transformation. Whereas in the past we’ve developed tests for whether a human is fit to do something, in this new world we need a new set of tests to assure autonomous systems and build a bridge of trust. This is not a one-off test, it is ongoing work to develop new methodologies and support the development of new standards.

“One of the key things this country has developed is Testbed UK, a collaboration between government and industry which has delivered a formidable testing environment – a network of safe, highly controlled environments increasingly linked to virtual testing.

“Working with the Met Office on behalf of the Centre for Connected and Autonomous Vehicles (CCAV) over the last year we have focused on the usability and reliability of sensors in different weather conditions. How do you know if sensors are performing well? How do you validate the decision making? How do you apply metrics and KPIs to this? Having undertaken a proof of concept for a testing framework, we are confident this can be delivered and deployed throughout the industry.

“There is much talk about pass/fail tests but our focus is confidence, improving confidence in the outputs and building confidence in the system. We collaborate across the board, with regulators, testers, developers – engaging with them to understand their requirements.  Our approach is to provide tools which help reduce the barriers to innovation without compromising regulation and safety assurance.  Striking the right balance between reliability and usability is key. Our work will support validation and help the UK to influence international standards.

“The biggest transformation in road transport over the next decade will be emissions reduction and self-driving vehicles and smart mobility systems will be key drivers. It will require changes to infrastructure and changes in habits – batteries or hydrogen will be critical, perhaps a need to drive more slowly, maybe less private car ownership. The impact of Covid has led to a move away from trains and buses, so a resurgence of public transport is vital.

“In terms of self-driving, I envisage there will be personally driven vehicles and on-demand vehicles. Increasingly I expect we’ll see a transition into smaller public transport vehicles, perhaps for 8-10 people, in continuous use. There’s real value in getting to places that don’t have bus stops and there’ll be benefits from autonomous safety features too. It won’t be everywhere but I hope within 10 years there’ll be good examples of that in the UK. The question is will we be ahead or behind the curve? In some more authoritarian countries implementation might be faster but maybe not better.

“We’ll also start to see autonomous low level aviation and autonomous shipping, for example, short cargo sea freight. Combined, these things will make roads less congested. Key transport stakeholders have expressed the need to integrate, to pursue the most efficient way to get goods into and around the UK.

“For our part, we are focused on the framework for virtual sensor testing, and also integration between virtual and physical testing. To give an accurate level of confidence requires understanding the common metrics and the areas of uncertainty. The human factor is so important, for example, what about the people with cars that don’t have this tech – how do they respond?”

For further info visit www.npl.co.uk.

Vivacity Labs founder backs the citizen first vision of 21st century privacy.

Time for a grown-up conversation about cameras, AI, traffic flow and privacy

Our Zenzic CAM Creator series continues with the founder of Vivacity Labs, Mark Nicholson.

Vivacity uses sensors, cameras and artificial intelligence (AI) to provide “up-to-the-minute data on urban movement”, helping local councils to promote active travel, improve safety and reduce congestion. Big Brother you say? Well, it’s 2020 not 1984 and CEO Mark Nicholson is very happy to have that debate.

MN: “As the transport network becomes more complicated, local authorities need more powerful tools. Tech giants have invaded the ecosystem, and when you’re dealing with Uber and driverless cars, sending someone out with a clipboard just isn’t going to cut it. We bring new technology which tells them about their transport, so they can adapt and gain control over the ecosystem.

“We started with sensors and then video-based sensors, generating huge data sets and better quality data. We’ve looked at everything from cyclists undertaking to lockdown journey times and asked: how can we use this data to make the road system more efficient? The next phase is autonomous vehicles, because that ecosystem needs to work with both infrastructure and other road users.

“Privacy is not just a key issue in self-driving but in the whole smart city. There are basically two visions – the Chinese and the European. The Chinese vision is very invasive, it’s 1984 and that’s the point. The alternative is the European vision, with the General Data Protection Regulation (GDPR). For a while it looked like there might be a third, a corporate American vision. Google were running a smart city project in Canada, but it didn’t work out so we’re back to two models.”

If you don’t know about the Quayside project in Toronto, a much-shared Guardian article from 2019 warned of surveillance capitalism, data harvesting and the possibility that algorithms could be used to nudge behaviour in ways that favour certain businesses. You can read it here or, er, Google it.

MN: “We’re very much on the European, privacy-centric, citizen first side – an ecosystem that gives the benefits of mass data without the costs to privacy. All our data is anonymised at source, everything. Each camera or sensor unit has its own processor on board which uses AI to extract information, for example, what are the road users? The imagery is discarded within a few milliseconds, all we keep is the data. We recently looked at how socially distanced people were in Kent and, although no personal data was collected, it caused a bit of controversy.”

It did indeed. “Big Brother is watching your social distancing: Fury as traffic flow cameras are secretly switched to monitor millions of pedestrians in government-backed Covid project”, screamed the headline in the Daily Mail. We’d better get back to self-driving.

MN: “Over the last couple of years the hype around driverless cars has died down. There’s been a recognition that autonomous vehicles are not as close as Elon Musk promised. The technology is progressing though. They can drive quite well on motorways and in quiet areas, but in busy, congested areas they struggle.

“What would happen if you rolled out driverless cars today? My suspicion is they would probably perform to about the same level as human drivers. The question is: Are we happy with systemic risk rather than personal risk? Can we engineer out that risk? Can we make the infrastructure intelligent enough so it works with vehicles in even the most challenging situations?

“The best way to end the no-win scenario is to have enough data to dodge it. Most of these incidents come about due to an unforeseen element, such as a pedestrian stepping out, a cyclist skipping a red light or someone speeding round a corner. If the vehicle knows about it in advance, the trolley problem never occurs. For me it’s about having the data earlier, and how we, as representatives of infrastructure, can help to give cars that information.”

For further info, visit vivacitylabs.com.

Shock news: driverless cars threaten driving jobs

The impact of automation and artificial intelligence (AI) on jobs is a hot topic this week.

In Northern Ireland, a study by the Nevin Economic Research Institute (NERI) concluded that 58% of jobs are at risk of “substantial change” due to advances in AI, robotics and other technologies.

The report highlighted a re-emergence of ‘automation anxiety’ and concerns about the future of work.

However, it also asserted that “while automation may destroy some jobs, an equal or greater number of jobs will likely be created in the aftermath.”

Nice use of “likely”.

In India, The News Minute reported on a keynote speech by the country’s Telecom Secretary, Aruna Sundararajan.

“Adoption of digital technology has proved to be a great democratiser and leveller,” she said. “But digital is also throwing up many challenges and there are no easy answers to them.

“There are various estimates about the rate at which jobs are becoming irrelevant – from 10% to a high of 70%.”

Sundararajan suggested that a universal basic income could be part of the solution.

“The idea of providing universal basic income is gaining ground because a lot of Silicon Valley leaders are pushing for it,” she said.

In the UK, research by MoneySuperMarket found that automation of driving jobs could trigger large-scale redundancies by as early as 2023.

Seán Kemple, director of sales at Close Brothers Motor Finance, noted: “The courier service industry is already anticipating huge changes, particularly for last-mile delivery, and not much further down the line the taxi industry is likely to change too.”

One reassuring point which cropped up in the University of Michigan’s Self-Driving Cars Teach-Out was the continuing need for humans in roles variously described as operators, attendants, concierges or guides.

This dovetails with a recent Opinium survey for Enterprise Rent-A-Car, which found that 77% believe driverless vehicles in the UK should have someone ready to take the wheel.

Ben Lawson, vice president of mobility and project development at Enterprise Rent-A-Car UK, said: “There are many elements that will determine when driverless cars become mainstream including the technology itself, consumer attitudes, affordability and public policy.”

Something akin to the long-running argument about the need for train guards seems – to coin a phrase – likely.