One of the questions that we at the International Data Corporation are asked is what impact technologies like Artificial Intelligence (AI) will have on jobs. Where are there likely to be job opportunities in the future? Which jobs (or job functions) are most ripe for automation? What sectors are likely to be impacted first? The problem with these questions is that they misunderstand the size of the barriers in the way of system-wide automation: the question isn’t only about what’s technically feasible. It’s just as much a question of what’s legally, ethically, financially and politically possible.
That said, there are some guidelines that can be put in place. An obvious career path exists in being on the ‘other side of the code’, as it were – being the one who writes the code, who trains the machine, who cleans the data. But no serious commentator can leave the discussion there – too many people are simply not able to or have the desire to code. Put another way: where do the legal, financial, ethical, political and technical constraints on AI leave the most opportunity?
Firstly, AI (driven by machine learning techniques) is getting better at accomplishing a whole range of things – from recognising (and even creating) images, to processing and communicating natural language, completing forms and automating processes, fighting parking tickets, being better than the best Dota 2 players in the world and aiding in diagnosing diseases. Machines are exceptionally good at completing tasks in a repeatable manner, given enough data and/or enough training. Adding more tasks to the process, or attempting system-wide automation, requires more data and more training. This creates two constraints on the ability of machines to perform work:
- machine learning requires large amounts of (quality) data and;
- training machines requires a lot of time and effort (and therefore cost).
Let’s look at each of these in turn – and we’ll discuss how other considerations come into play along the way.
Speaking in the broadest possible terms, machines require large amounts of data to be trained to a level to meet or exceed human performance in a given task. This data enables the bot to learn how best to perform that task. Essentially, the data pool determines the output.
However, there are certain job categories which require knowledge of, and then subversion of, the data set – jobs where producing the same ‘best’ outcome would not be optimal. Particularly, these are jobs that are typically referred to as creative pursuits – design, brand, look and feel. To use a simple example: if pre-Apple, we trained a machine to design a computer, we would not have arrived at the iMac, and the look and feel of iOS would not become the predominant mobile interface.
This is not to say that machines cannot create things. We’ve recently seen several ML-trained machines on the internet that produce pictures of people (that don’t exist) – that is undoubtedly creation (of a particularly unnerving variety). The same is true of the AI that can produce music. But those models are trained to produce more of what we recognise as good. Because art is no science, a machine would likely have no better chance of producing a masterpiece than a human. And true innovation, in many instances, requires subverting the data set, not conforming to it.
Secondly, and perhaps more importantly, training AI requires time and money. Some actions are simply too expensive to automate. These tasks are either incredibly specialised, and therefore do not have enough data to support the development of a model, or very broad, which would require so much data that it will render the training of the machine economically unviable. There are also other challenges which may arise. At the IDC, we refer to the Scope of AI-Based Automation. In this scope:
- A task is the smallest possible unit of work performed on behalf of an activity.
- An activity is a collection of related tasks to be completed to achieve the objective.
- A process is a series of related activities that produce a specific output.
- A system (or an ecosystem) is a set of connected processes.
As we move up the stack from task to system, we find different obstacles. Let’s use the medical industry as an example to show how these constraints interact. Medical image interpretation bots, powered by neural networks, exhibit exceptionally high levels of accuracy in interpreting medical images. This is used to inform decisions which are ultimately made by a human – an outcome that is dictated by regulation. Here, even if we removed the regulation, those machines cannot automate the entire process of treating the patient. Activity reminders (such as when a patient should return for a check-up, or reminders to follow a drug schedule) can in part be automated, with ML applications checking patient past adherence patterns, but with ultimate decision-making by a doctor. Diagnosis and treatment are a process that is ultimately still the purview of humans. Doctors are expected to synthesize information from a variety of sources – from image interpretation machines to the patient’s adherence to the drug schedule – in order to deliver a diagnosis. This relationship is not only a result of a technicality – there are ethical, legal and trust reasons that dictate this outcome.
There is also an economic reason that dictates this outcome. The investment required to train a bot to synthesize all the required data for proper diagnosis and treatment is considerable. On the other end of the spectrum, when a patient’s circumstance requires a largely new, highly specialised or experimental surgery, a bot will unlikely have the data required to be sufficiently trained to perform the operation and even then, it would certainly require human oversight.
The economic point is a particularly important one. To automate the activity in a mine, for example, would require massive investment into what would conceivably be an army of robots. While this may be technically feasible, the costs of such automation likely outweigh the benefits, with replacement costs of robots running into the billions. As such, these jobs are unlikely to disappear in the medium term.
Thus, based on technical feasibility alone our medium-term jobs market seems to hold opportunity in the following areas: the hyper-specialised (for whom not enough data exists to automate), the jack-of-all-trades (for whom the data set is too large to economically automate), the true creative (who exists to subvert the data set) and finally, those whose job it is to use the data. However, it is not only technical feasibility that we should consider. Too often, the rhetoric would have you believe that the only thing stopping large scale automation is the sophistication of the models we have at our disposal, when in fact financial, regulatory, ethical, legal and political barriers are of equal if not greater importance. Understanding the interplay of each of these for a role in a company is the only way to divine the future of that role.
How tech is keeping us young
Research by Lenovo revealed people who use tech feel, on average, 11 years younger.
Technology is making the world feel younger, healthier and more emotionally connected, reveals new research by Lenovo, suggesting a growing relationship between technological innovation and wellbeing.
The research, which surveyed over 15,000 individuals from around the globe, from the US, Mexico, Brazil, China, India, Japan, UK, Germany, France and Italy, not only found 40% of global respondents feel “a lot” or “somewhat” more youthful thanks to technology, but on average it made them feel younger by 11 years.
This rings most true in China, where 70% of Chinese respondents said technology made them feel more youthful, which could be perhaps due to technologies ability to build connections between generations, especially those who might have once felt disconnected from tech-savvy youngsters. For example, grandparents are now able to better communicate with their grandchildren via smart technology due to its growing ubiquity and ease of use.
The research suggests that this sentiment is felt world-over, across genders and ages. “To know how to operate newer technology makes me feel younger” one US woman, said. Another woman, from France, also stated, “Compared to the younger generation who are born with all these technologies, my adaptability makes me feel younger”. On the other side of the globe, one female respondent in India cited tech as making her feel like she “can do anything with it which any youngster can do,” and one Chinese male respondent said: “It helps me catch up with the times – not only gaining more knowledge, but also feel that I’m on-trend; I feel younger”.
The research generally revealed that many older generations think using technology helps them to connect better with younger people as well as feel livelier and more knowledgeable. This is especially evident when it comes to the role smart devices (from PCs, tablets to smart home assistants and more) play in terms of relationships with family and friends. When asked to compare technology today to those of 20 years ago for giving them the ability to feel connected to what is going on in the lives of the people they care about, 65 percent answered it’s “getting better”. While 75% also said technology is improving their ability to stay in touch with family and friends who live far away.
The global research also revealed that tech is helping people when it comes to mental health and wellbeing, offering emotional gains, particularly in parents. Over three-quarters (78%) of working parents stated the ever-connected nature of technology helps them feel more emotionally connected to their children, even when they are away from home. An even larger portion (83%) of working parents agreed that emerging technologies are making it easier for them to feel confident that their kids are safe and secure while they are at work.
Over two-thirds (67%) of respondents in the survey stated they were optimistic about the future of technology and the role tech can play in our lives and society, especially in wellbeing, with 67% believing devices are currently having a positive impact on the ability to improve their overall health. And that’s hardly surprising, considering 84% also said tech has empowered them to make improvements in their lives overall.
Take for instance how one respondent, a 51-year-old woman from the US, highlighted how science is using technology to do great things for amputees, and enabling those suffering from mental illness to better connect with people from all over the world. “I think that the medical breakthroughs we’ve had are a tremendous statement on how we can have a positive relationship with technology,” she said.
The recognition that tech is helping to improve the quality of life could also be a result of the time it tends to save people. Half of respondents across all markets (50%) feel their smart devices save them 30 minutes or more a day by helping them do something faster or more efficiently. Similarly, over half (57%) agreed smart devices, such as computers and smart home devices like smart displays and smart clocks, are making them more productive and efficient, the highest perceptions of which were seen in China at 82% and India at 81%.
In terms of personal health, 36% of respondents said smart devices have made it easier for them to access health care providers and make doctor’s appointments, and a further 39% of those under 60 years of age stated modern tech makes it easier for seniors to contact emergency services.
A 23-year-old woman from India, for example, expressed her belief that the technological advancement of medical science is helping people better fight diseases and potentially cure them. “Lives of people are better off nowadays because they know ways of curing such health hazards,” she said. “Through technology, increasing the life span of an individual is very much possible.”
Psychologist and founder of Digital Nutrition, Jocelyn Brewer, said: “Keeping up with advancements in technology can feel like a full-time job, but it can have positive impacts on people’s sense of themselves and their age. While older people are stereotyped as being techno-phobic or inept at staying on-trend, this research points to the fact that maintaining currency in the digital space helps people feel more youthful, more connected to young people and youth culture, which in turn is a social currency for feeling valued and a sense of belonging or in ‘the know’.
“It’s this tech knowledge that drives the perception of feeling younger, without having to revisit the angst of our adolescence!
“Staying connected to the people we care about is a wonderful feature of technology. And while it is no replacement for face-to-face connection, it is a valuable supplement to communication for those who might be geographically divided. Parents can manage a range of responsibilities and provide increasing appropriate autonomy to teenagers through a variety of communication tools, reminders and systems that can help take the struggle out of the daily juggle.”
Dilip Bhatia, Vice President of User and Customer Experience, Lenovo, said: “There is a growing relationship between innovation and wellbeing as smart technologies are not only helping people globally to stay more connected but aiding wellbeing in the form of compassion and empathy by building better connections between them.”
“Technology has a transformational ability to unite people across generations and walks of life around the world, with the potential to help them to live healthier and more fulfilling lives. At Lenovo, we passionately believe in creating smarter technology for all, which is why we focus on making our technology accessible, blending into the everyday lives for the benefit of more people.”
Advanced traffic management tech market hits $1bn
A new report from Navigant Research analyzes the ongoing transformation occurring in the traffic management industry, providing global market forecasts, segmented by region and technology, through 2028.
Advanced traffic management systems (ATMSs) such as adaptive traffic control (ATC) are enabling greater efficiencies in the traffic management ecosystem and can help integrate the expected growth in vehicle populations without overwhelming existing infrastructure. ATMSs are also enabling the development of smart intersections, which are emerging as one of the most important data-driven backbones needed for solving core city challenges. Click to tweet: According to a new report from Navigant Research, the global market for advanced traffic management will be worth more than $1.1 billion in 2019. Annual revenue is expected to grow to nearly $3.8 billion by 2028, representing a compound annual growth rate (CAGR) of 14.2%.
“The global advanced traffic management market is expected to more than triple by 2028,” says Ryan Citron, senior research analyst with Navigant Research. “Over the next 10 years, the market is expected to achieve gradual but accelerating growth as cities prioritize reducing traffic congestion and greenhouse gas emissions, make improvements in safety and livability, and integrate ATMSs with other smart city initiatives (e.g., smart street lighting).”
Currently, cities vary in their level of maturity in using ATMSs. Collecting traffic and vehicle detection data is often the first step toward advanced traffic management. Then, in-depth traffic analytics enable traffic managers to develop mitigation strategies and make operational improvements to existing traffic signal timing systems. In cities with mature traffic management solutions, ATC technologies enable traffic signals to adjust based on real-time traffic conditions, traffic data is sent from traffic lights to connected vehicles, inter-agency data sharing is on the rise, and transport platforms are used to manage mobility ecosystems.
The report, Advanced Traffic Management for Smart Cities, analyzes the ongoing transformation occurring in the traffic management industry. The study focuses on ATC, traffic analytics, artificial intelligence, vehicle-to-infrastructure communications, and vehicle detection technologies. Global market forecasts, segmented by region and technology, extend through 2028. This report also explores regional trends in advanced traffic management strategy and highlights city case studies where innovative projects are being deployed. An Executive Summary of the report is available for free download on the Navigant Research website.