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Stanford University Study Looks at AI Impact on Urban North America: Life in 2030 Part 1

September 6, 2016

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September 6, 2016 – Artificial Intelligence or AI includes a constellation of technologies including computer vision, machine learning, natural language processing, neural networks and other pattern recognition computer capabilities. In the latest Stanford University study focused on the next one hundred years researchers examine long-term AI impacts. Overseen by a panel of experts the larger study of which this first one looking at urban life impacts examines:

Transportation – autonomous vehicles from ground to air including service delivery AI robotics
Service robots – from today’s vacuum cleaners to home security and environmental management AI systems
Healthcare – from today’s surgical robots to provision of patient care
Education – from enhanced classroom learning to personalization of education using machine tutors
Low-resource communities – from data mining and machine learning to address at-risk members to AI robotics engaged in delivering community services
Public safety and security – from drone border patrols to algorithms that detect fraud and provide predictive policing
Employment and workplace – from lowering the cost of producing goods and services, to the rethinking of wealth creation and social safety nets that ensure a base income for all regardless of work status
Entertainment – from information retrieval and processing to AI generated music and plays generating immersive and interactive 3D.

We will look at the above more closely later in this posting. But first it should be noted that the study found “no cause for concern that AI is an imminent threat to humankind.” So for those who see AI through the lens of an Elon Musk or Stephen Hawking who have warned us all about its inherent evil, the Stanford research team found no machine technology developed or under consideration as likely to be developed to resemble a Skynet from the Terminator movies, or the AI of the Matrix. Instead the study refers to potential positive and negative impacts of AI on urban North American society by 2030. The study does not gloss over disruption from AI. Instead it sees this as a new challenge for the economy and society and recognizes that researchers and developers of AI must balance innovation with “mechanisms to ensure that AI’s economic and social benefits are broadly shared across society.”

What are the hot areas of AI technological development that will most impact urban life in North America by 2030?

Large-scale machine learning – working with large data sets to derive meaningful information that can be expedited quickly
Deep learning – training AI technologies to better recognize objects and activities
Reinforcement learning – moving from pattern recognition and mining to helping AI to learn from experience-driven sequences
Robotics – advancing machine perception from visual to tactile reinforced by all of the above technologies
Computer vision – enhancing visual classification and machine perception
Natural language processing – combined with automatic speech recognition to enhance interaction with people through unstructured dialog
Collaborative systems – to develop AI autonomy in conjunction with working beside and with humans as effective partners
Internet of Things – to interconnect, collect and share a wide range of sensory information and apply AI to it all to organize the babel
Neuromorphic computing – to incorporate characteristics of biological neural networks into the hardware that incorporates AI

Add to this crowdsourcing and human computation and the creation of collective wisdom knowledge repositories that AI and humans can contribute to and access, and advancements in algorithmic game theory and you have a very different urban landscape emerge.

The AI-influenced urban world of 2030 is already coming into shape. We are on the threshold of autonomous urban transportation in its various forms. With that urban dwellers will be less likely to own their own vehicles. A proliferation of sensors and cameras will alter our road networks. Autonomous vehicles will be interconnected to optimize traffic flow. On sidewalks autonomous wheeled-robots will navigate pedestrian traffic to deliver goods and services. Flying autonomous drones will also serve to deliver products to customers. On demand transportation will have reached a point of wide adoption from cars and boats to quadcopters.

Homes will continue to see an AI invasion from the trilobite-like Roomba vacuum cleaners to more sophisticated home robots capable of delivering a range of services. Advances in speech recognition will make the interaction of AI-empowered devices with humans in homes very natural. We can already see the rise of social interaction robots in Japan and through enhancements these should become ubiquitous in urban home life by 2030.

In healthcare whether in clinical setting, surgeries, or through advanced analytics we should see a significant impact on how patients interact with providers of health services. The largest impact may be in the field of elder care with North America’s greying population. AI will be applied to assisting humans with life quality and independence, with early detection of potential health threats, and with the provision of better devices to deal with sensory loss such as vision and hearing.

In education the urban learning world of 2030 will incorporate teaching robots to accompany human teachers in schools. In homes robotic tutors will help students to learn. Online learning resources plus advances in analytics will identify students at risk providing guidance and customized learning to improve educational outcomes. The implementation of AI will blur the lines between formal education and individual self-directed learning. Books will continue the transition to digital media and texts will become individualized to meet specific learning objectives. In addition machine translation will make educational materials multi-lingual eliminating language understanding as a barrier to learning.

AI technologies will have a significant impact on those urban areas defined as low-resource. AI cna be applied to address joblessness and other social problems by providing insights through data science for social good. Predictive modeling will assist government agencies to prioritize citizens at risk because of health. sanitation, disease, nutrition, domestic abuse, homelessness and inadequate housing, and lack of community programs focused on healthy socialization. Applied AI will help eliminate discriminatory practices in the delivery of these essential services.

Today AI is already being deployed for public safety and security in North American urban centres. Whether applied to policing or through analytics applied to detect anomalies pinpointing potential crime, AI will alter public trust of our security apparatus. AI today is already helping to detect credit card fraud. Further improvements to machine learning and pattern recognition using AI will help to manage crime scenes, search and rescue, and through better predictive tools thwart urban terror. Combined with the widespread use of cameras AI capable of high-speed and efficient processing of video images to detect anomalies will greatly improve safety and security. AI tools will assist law enforcement through immersive 3D interactive training. The monitoring of social media using AI tools will help to identify legitimate risk concerns.

The greatest impact of AI is in the area of the workplace and employment. Automation has already produced positive and negative effects. Globalization has distorted urban economies even further. AI will definitely take away many jobs will introducing new types of labour and skills demand that will require a different workforce. Whether AI is applied to production lines or law offices, the impact will be felt. Human fears of being marginalized need to be addressed. Taxi and bus drivers are among the most obvious to be impacted by AI as implemented in autonomous and on-demand transportation. Delivery service jobs will disappear. The loss of jobs will impact quality of life unless governments create political changes that address economic displacement. Social safety net policy will by necessity require alteration. Continuous learning assisted by AI will serve to help urban citizens transition to new employment opportunities. A guaranteed basic income, once thought as radical, may be instituted as a means by which the dividends of AI become equally shared across urban society.

In entertainment AI will enable the further advancement of user-generated content from social media and other sources. AI can help to facilitate creativity in new forms using tools that generate 3D scenes from written text, or visually recreate the results of historic research. And AI will be able to mine the aggregated digital content of the Internet to personalize the delivery of news and information. The traditional newspaper as we know it will vanish. Libraries will evolve to become digital repositories that AI tools will help to mine for readers. For marketers, advertisers and retailers AI will serve them to better understand consumer preferences and usage providing micro-analysis of buyer behaviour. Some would say this last capability will not better the urban environment of 2030.

In part two describing the results of the Stanford study we’ll look at what the researchers have defined as prospects and recommendations on AI public policy based on their 2030 projections.