Universities and the digital transformation of society
Our smartphones have apps that help us navigate traffic, find public transportation or book rides in cabs. The “sharing” economy is enabling us to change how we find hotel rooms when we travel, and how we get loans or fund new businesses. These are just a few examples of how our daily lives have undergone a digital transformation that is bringing us a dizzying array of new choices as well as launching new business models.
Transportation and travel are just two of many sectors that are going through this radical transformation. For example, in healthcare, personal medical records and genomic data are already digital. Now, with the monitoring of people by wearable and implanted devices that remotely monitor pulse, blood chemistry, hormone levels, blood pressure, temperature, EMG and even EEG, we can provide levels of personalized medicine that were unimaginable even a few years ago.
Another example is in retail, where Amazon is digitally transforming how we shop. Enel, the world’s largest electric power utility, is using the Internet of Things (IoT), predictive maintenance and fraud detection to drive new levels of reliability, cost efficiency and clean energy in Europe. Oil and gas operators are using predictive maintenance to monitor production assets and predict and prevent device failures from submersible oil pumps on offshore oil rigs. Manufacturers like Caterpillar are using IoT systems to lower inventory, production and delivery costs. Driving these changes is the confluence of the following technology trends: IoT, machine learning and artificial intelligence (AI), and cloud computing.
Driven by the dynamics of Moore’s Law, a thriving multi-trillion information technology industry has created an Information Age that was foretold in 1973 by Harvard sociologist Daniel Bell. In the next 10 years, according to industry estimates, value chains will be sensorized: more than 70 billion sensors will have been installed across all sectors to provide unprecedented volumes of data that can be inexpensively stored and processed, enabling the utilization of computer-intensive machine-learning algorithms. AI is rapidly growing, and even though it is still in its relative infancy, it is poised to make major new advances.
The trifecta of IoT, AI and cloud computing offers a vision of digital transformation that is literally changing business models, services and how we live.
How universities can help
While the term digital transformation is a concept that is increasingly appearing on corporate board agendas, it is our responsibility in academia to ensure that we continue to grow the seed corn for continued innovation in AI, IoT and computing. Indeed, in addition to cloud computing, we will need to provide new solutions for high-performance computing at the edges to allow the kind of massive computations that are needed to power the analytics that are at the heart of this transformation.
Never has there been a greater need for user-inspired basic research … there are important public good and social justice issues that need to be addressed.
Never has there been a greater need for user-inspired basic research. In addition, there are important public good and social justice issues that need to be addressed: privacy, pricing, societal, legal and economic issues are at the forefront. For instance, it is important that pricing of new services not be regressive, or that other derived information not result in the inadvertent disclosure of private information.
On the public policy front, as Joan Walker, professor of civil and environmental engineering, says, we need to move away from an era where infrastructure policy was set by state and local governments exclusively. We are entering an era where intelligent information infrastructure is a shared public-private partnership.
At the same time, we will need to address the job churn being created by this transformation. For example, Uber and Lyft have created an entirely new mode of transportation using IoT and the cloud. These companies have disrupted traditional taxi and limo industries. Their impact has been felt as several traditional cab companies have declared bankruptcy, resulting in a glut of city-issued taxi medallions. This scenario is being played out in multiple job sectors.
It is our mission in the university to take the lead in providing lifelong learning solutions and refreshers to enable our workforce to both keep current and also seek new opportunities. Our menu of professional masters courses and short courses, like the Engineering Leadership Professional Program, need to be expanded to address these needs.
Then, of course, there are legal issues associated with the regulation of robotic systems working in close proximity with humans. A few years ago, we relegated robots exclusively to jobs that were considered dull, dirty and dangerous. However, this is no longer the case, as we see in factory automation, drone delivery systems or self-driving cars. The questions of how we endow self-driving cars with the ability to make decisions are certainly upon us with the investigations of recent accidents involving driverless cars.
“We’re in a whole new space. Industry is moving quickly — sometimes too quickly — and the government is left trying to catch up with policy and regulations. This is why universities need to step in. We have expertise in the implications for the fast moving changes taking place, and we can inform policy as the technology rolls out.”
– Joan Walker, professor of civil
and environmental engineering
Can AI be made safer? Claire Tomlin, professor of electrical engineering and computer sciences, has begun the study of verifiable and safe AI to provide guarantees of how well humans and robots can work together based on developing human cognitive models. On the policy front, Tomlin is working with the Federal Aviation Administration, NASA and other certification authorities to designate airways in the sky to enable commercial drone operations.
“We’re in a whole new space,” says Walker. “Industry is moving quickly — sometimes too quickly — and the government is left trying to catch up with policy and regulations. This is why universities need to step in. We have expertise in the implications for the fast-moving changes taking place, and we can inform policy as the technology rolls out.”
The Berkeley DNA
There are many reasons why Berkeley is well-poised as a leader in this regard. Not only is this campus at the forefront of research in IoT, AI and societal scale systems, it hosts world-class departments in economics, business, public policy, neuroscience, cognitive science and more. Berkeley’s thriving interdisciplinary ecosystem is a key to the success of this public university.
Faculty from economics and the Haas School of Business have been working hand in hand with technologists at the very forefront of the theory of mechanism design to offer new services that will benefit the public at large, not just a select few.
In another example, in the Health@Home initiative, industrial engineers and bioengineers are partnering with campus colleagues from economics, business, public health and policy to build a sustainable model of healthcare infrastructure. The goal is to reduce hospital visits with new tools for monitoring, screening and care to be used at home (or work, or school), but to do so without jeopardizing the sensitive personal data collected and stored in this system.
We house one of the world’s most comprehensive research groups in AI and machine learning, and they are brought together in the Berkeley Artificial Intelligence Research Lab where researchers tackle issues of privacy, cybersecurity and resilience alongside the development of new deep learning algorithms that allow robots to master skills via trial and error.
Earlier this year, the National Science Foundation granted $10 million to Berkeley for the Real-Time Intelligent Secure Explainable Lab, or RISELab, to build AI decision systems to address the challenges inherent when artificial intelligence plays an increasingly central role in healthcare, transportation, business and other aspects of our lives.
The goal is to invent the future in a way that supports the healthy development of our societies and economies in an age of intelligent tools.
There is no doubt that new automation needs to work closely with humans, and it needs to have models of human cognition and decision-making built in and that work collaboratively. As Tomlin says, “Not only will we need to have robots working with humans, but we will also need to embed humans in the midst of automation with provably correct outcomes.”
“The real question is not whether this will transform our society and culture, but how it will do so,” adds Ken Goldberg, professor and chair of industrial engineering and operations research. “And what are the human consequences in these rapid changes?”
Those are the types of hard questions being addressed through an initiative led by Goldberg called the People and Robots Initiative at CITRIS, the Center for Information Technology Research in the Interest of Society, as well as a new interdisciplinary group, Work and Intelligent Tools and Systems, or WITS.
The goal of these groups is to invent the future in a way that supports the healthy development of our societies and economies in an age of intelligent tools. The organizers include researchers from engineering, data science, economics, sociology and political science.
The benefits of digital transformation are breathtaking: A 2015 McKinsey Global Institute report estimates that the value that industries and governments will create from IoT Digital Transformation will range from $3 trillion to $11 trillion per year in 2025.
Our challenge going forward is to meld these new technologies with economic, business, legal, behavioral and many other tools and advances to design a society we will be glad to live in, even in the face of dramatic changes in how we work and live. This indeed will be our mantra going forward in Inventing the Future.