"Artificial intelligence (AI) is on a winning streak," assert Daniel Castro and Joshua New (@Josh_A_New), authors of a new report from the Center for Data Innovation.[1] They add:
"AI is already having a major positive impact in many different sectors of the global economy and society. For example, humanitarian organizations are using intelligent chatbots to provide psychological support to Syrian refugees, and doctors are using AI to develop personalized treatments for cancer patients. Unfortunately, the benefits of AI, as well as its likely impact in the years ahead, are vastly underappreciated by policymakers and the public. Moreover, a contrary narrative — that AI raises grave concerns and warrants a precautionary regulatory approach to limit the damages it could cause — has gained prominence, even though it is both wrong and harmful to societal progress."
Clearly, Castro and New believe the upside potential of artificial intelligence applications far outweigh the downside possibility that an AI system will someday attempt to take over the world and destroy mankind.
Defining Artificial Intelligence
Castro and New explain, "AI is a field of computer science devoted to creating computing machines and systems that perform operations analogous to human learning and decision-making." They continue:
"As the Association for the Advancement of Artificial Intelligence describes it, AI is 'the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines.' ... The level of intelligence in any particular implementation of AI can vary greatly, and the term does not imply human-level intelligence. AI involves many functionalities, including but not limited to: a) learning, which includes several approaches such as deep learning (for perceptual tasks), transfer learning, reinforcement learning, and combinations thereof; b) understanding, or deep knowledge representation required for domain-specific tasks, such as cardiology, accounting, and law; c) reasoning, which comes in several varieties, such as deductive, inductive, temporal, probabilistic, and quantitative; and d) interaction, with people or other machines to collaboratively perform tasks, and for learning from the environment."
Not clear in the Castro/New definition of artificial intelligence is that there are both narrow and broad (or weak and strong) applications of AI. The broad version is more commonly referred to as artificial general intelligence (AGI) and is the application that some pundits warn could lead to humanity's downfall. To date, only narrow applications of artificial intelligence have been developed and these applications are the ones which Castro and New discuss in their report. As they note, "The level of intelligence in any particular implementation of AI ... does not imply human-level intelligence." They do go on to note, "The cause of many misconceptions about AI, particularly its potential harms, is the difference between weak AI and strong AI. Weak AI, which is the focus of this report, is adept at performing particular types of tasks, but only those types of tasks — somewhat like a technological savant."
The field of artificial intelligence receiving the most press coverage (thanks to IBM's Watson) is cognitive computing. Cognitive computing is a powerful, but narrow, form of AI. There is no single method (or accepted definition) of cognitive computing, although all cognitive computing systems do share a few characteristics including natural language processing and machine learning. The Enterra Solutions® entry in this field is the Enterra Enterprise Cognitive System™ (ECS) — a system that can Sense, Think, Act, and Learn®. At Enterra®, we define cognitive computing as a combination of Semantic Intelligence (Artificial Intelligence + Natural Language Processing) combined with Computational Intelligence (Advanced Mathematics). As noted below, narrow applications of AI, which include cognitive computing systems, hold great promise for improving life on the planet.
The Value of Artificial Intelligence
Value can be defined in many ways from economic value to social good. Castro and New report, "Because AI will continue to evolve and work its way into a wide variety of applications, it is difficult to predict just how much value AI will generate. The International Data Corporation estimates that in the United States the market for AI technologies that analyze unstructured data will reach $40 billion by 2020, and will generate more than $60 billion worth of productivity improvements for businesses in the United States per year. ... The social benefits of AI are similarly substantial, though harder to quantify. ... AI is already delivering valuable social benefits today, such as by helping authorities rapidly analyze the deep web to crack down on human trafficking, fighting bullying and harassment online, helping development organizations better target impoverished areas, reducing the influence of gender bias in hiring decisions, and more."
Castro and New note that AI can be used in at least seven different ways, including: monitoring; discovering; predicting; interpreting; interacting with the physical environment; interacting with people; and interacting with machines. The bulk of their report delves more deeply into these areas by discussing 70 examples of artificial intelligence in use in 14 categories: accessibility; agriculture; business operations; consumer convenience; disaster prevention and response; education; energy; environment; health care: prevention and screening; health care: treatment and monitoring; industrial operations; public safety; social good; and transportation. If you are interested in how artificial intelligence can be leveraged in a positive way, I encourage you to read the full report. Below is a list of the 14 categories and the examples discussed under those categories by Castro and New.
Accessibility
Making the Internet more accessible for people with visual impairments
Helping people understand sign language
Gamifying emotional recognition
Making it easier to get around in a wheelchair
Identifying dangerous sounds
Agriculture
Farming indoors autonomously
Learning as soon as plants get sick
Forecasting crop yields from space
Spot-treating crops
Making vegetable sorting easy
Business Operations
Predicting area-specific weather implications
Learning how to keep customers happy
Reducing gender bias in the office
Automating office assistants
Making customer support multilingual
Consumer Convenience
Deep learning for finding the right restaurant
Automating personalized finance advice
Creating robots that get emotional
Helping consumers buy what they like
Making it easier to sort photos
Disaster Prevention and Response
Predicting where earthquakes do the most damage
Keeping emergency responders out of danger
Detecting disease outbreaks
Understanding a crisis with social media
Avoiding dangerous solar flares
Education
Personalizing math class
Predicting which students will drop out
Automating teacher assistants
Making it easier to learn new languages
Giving students feedback in real time
Energy
Predicting renewable energy availability
Modeling energy consumption for more efficient buildings
Teaching a data center to make itself more efficient
Learning how to manage home energy use
Picking the best spot for a wind farm
Environment
Stopping deforestation before it starts
Predicting dangerous air pollution levels
Improving antipoaching efforts
Saving threatened birds
Teaching a robot to recycle
Health Care: Prevention and Screening
Preventing vision loss in diabetes patients
Predicting schizophrenia by analyzing speech
Figuring out how to prevent pancreatic cancer
Automating a microscope to diagnose malaria
Diagnosing voice disorders
Health Care: Treatment and Monitoring
Helping diabetes patients make smarter diet decisions
Streamlining drug discovery
Making stitches safer with robotic surgeons
Using AI to speed recovery
Increasing participation in clinical trials
Industrial Operations
Preventing breakdowns before they happen
Intelligent manufacturing to automate factories
Maximizing oil-well performance
Improving dairy supply chains with market forecasting
Making industrial design smarter
Public Safety
Pinpointing gunshots to fight crime
Predicting crime hotspots
Autonomously disposing of car bombs
Predicting buildings' fire risk
Making security screening less invasive
Social Good
Mapping poverty with satellite data
Measuring literacy rates
Cracking down on human trafficking
Stopping abusive Internet trolls
Supporting refugees' mental health
Transportation
Making public transportation autonomous
Platooning autonomous trucks
Hailing a self-driving taxi
Teaching trains to drive themselves
Making long-haul trucking easier
Summary
Castro and New note, "The examples in this report only scratch the surface of the many ways that AI is driving innovation in the public and private sectors, generating substantial social and economic value, and transforming everyday life around the globe. But as with any new technology, there will inevitably be detractors who fear change and how it might impact them." Their report is less than 50 pages, but packed with useful examples that could spark other ideas about useful ways artificial intelligence could be used. I highly recommend it for anyone interested in the subject.
Footnotes [1] Daniel Castro and Joshua New, The Promise of Artificial Intelligence, Center for Data Innovation, October 2016.