AI in healthcare. The biggest bets are on improving patient outcomes and
reducing
costs. Companies are applying machine learning to make better and faster diagnoses than humans. One
of the best-known healthcare technologies is IBM Watson. It understands natural language and can
respond to questions asked of it. The system mines patient data and other available data sources to
form a hypothesis, which it then presents with a confidence scoring schema. Other AI applications
include using online virtual health assistants and chatbots to help patients and healthcare
customers find medical information, schedule appointments, understand the billing process and
complete other administrative processes. An array of AI technologies is also being used to predict,
fight and understand pandemics such as COVID-19.AI in business. Machine learning algorithms are being integrated into analytics
and
customer relationship management (CRM) platforms to uncover information on how to better serve
customers. Chatbots have been incorporated into websites to provide immediate service to customers.
Automation of job positions has also become a talking point among academics and IT analysts.AI in education. AI can automate grading, giving educators more time. It can
assess
students and adapt to their needs, helping them work at their own pace. AI tutors can provide
additional support to students, ensuring they stay on track. And it could change where and how
students learn, perhaps even replacing some teachers.
AI in finance. AI in personal finance applications, such as Intuit Mint or TurboTax, is disrupting
financial institutions. Applications such as these collect personal data and provide financial
advice. Other programs, such as IBM Watson, have been applied to the process of buying a home.
Today, artificial intelligence software performs much of the trading on Wall Street.AI in law. The discovery process -- sifting through documents -- in law is often
overwhelming for humans. Using AI to help automate the legal industry's labor-intensive processes is
saving time and improving client service. Law firms are using machine learning to describe data and
predict outcomes, computer vision to classify and extract information from documents and natural
language processing to interpret requests for information.AI in finance. AI in personal finance applications, such as Intuit Mint or
TurboTax, is
disrupting financial institutions. Applications such as these collect personal data and provide
financial advice. Other programs, such as IBM Watson, have been applied to the process of buying a
home. Today, artificial intelligence software performs much of the trading on Wall Street.AI in banking. Banks are successfully employing chatbots to make their customers
aware
of services and offerings and to handle transactions that don't require human intervention. AI
virtual assistants are being used to improve and cut the costs of compliance with banking
regulations. Banking organizations are also using AI to improve their decision-making for loans, and
to set credit limits and identify investment opportunities.AI in transportation. In addition to AI's fundamental role in operating
autonomous
vehicles, AI technologies are used in transportation to manage traffic, predict flight delays,
and make ocean shipping safer and more efficient.
Regulation of AI technology
Despite potential risks, there are currently few regulations governing the use of AI tools, and
where laws do exist, they typically pertain to AI indirectly. For example, as previously mentioned,
United States Fair Lending regulations require financial institutions to explain credit decisions to
potential customers. This limits the extent to which lenders can use deep learning algorithms, which
by their nature are opaque and lack explainability.
The Europe Union's General Data Protection Regulation (GDPR) puts strict limits on how
enterprises can use consumer data, which impedes the training and functionality of many
consumer-facing AI applications.In October 2016, the National Science and Technology Council issued a report examining
the potential role governmental regulation might play in AI development, but it did not recommend
specific legislation be considered.
Crafting laws to regulate AI will not be easy, in part because AI comprises a variety
of technologies that companies use for different ends, and partly because regulations can come at
the cost of AI progress and development. The rapid evolution of AI technologies is another obstacle
to forming meaningful regulation of AI. Technology breakthroughs and novel applications can make
existing laws instantly obsolete. For example, existing laws regulating the privacy of conversations
and recorded conversations do not cover the challenge posed by voice assistants like Amazon's Alexa
and Apple's Siri that gather but do not distribute conversation -- except to the companies'
technology teams which use it to improve machine learning algorithms. And, of course, the laws that
governments do manage to craft to regulate AI don't stop criminals from using the technology with
malicious intent.
