Can AI really be worth $15.4 TRILLION?

McKinsey reported that total potential “annual value of AI and analytics across industries to be be worth $9.5 to $15.4 trillion” in its report entitled “The executive’s AI playbook” which includes 3 different perspectives:

Value & Assess – Size the opportunity and determine data needs

Execute – Learn best practices to realize value

Beware – Know the warning signed of AI program failure

The 3rd perspective to Beware includes 10 “warning signs of AI program failure” which are part of the May 2018 report “Ten red flags signaling your analytics program will fail” which includes #10 that “No one is hyperfocused on identifying potential ethical, social, and regulatory implications of analytics initiatives”:

It is important to be able to anticipate how digital use cases will acquire and consume data and to understand whether there are any compromises to the regulatory requirements or any ethical issues.

One large industrial manufacturer ran afoul of regulators when it developed an algorithm to predict absenteeism. The company meant well; it sought to understand the correlation between job conditions and absenteeism so it could rethink the work processes that were apt to lead to injuries or illnesses. Unfortunately, the algorithms were able to cluster employees based on their ethnicity, region, and gender, even though such data fields were switched off, and it flagged correlations between race and absenteeism.

Luckily, the company was able to pinpoint and preempt the problem before it affected employee relations and led to a significant regulatory fine. The takeaway: working with data, particularly personnel data, introduces a host of risks from algorithmic bias. Significant supervision, risk management, and mitigation efforts are required to apply the appropriate human judgment to the analytics realm.

First response: As part of a well-run broader risk-management program, the CDO should take the lead, working with the CHRO and the company’s business-ethics experts and legal counsel to set up resiliency testing services that can quickly expose and interpret the secondary effects of the company’s analytics programs. Translators will also be crucial to this effort.

Here are all Ten Red Flags:

  1. The executive team doesn’t have a clear vision for its advanced-analytics programs
  2. No one has determined the value that the initial use cases can deliver in the first year
  3. There’s no analytics strategy beyond a few use cases
  4. Analytics roles—present and future—are poorly defined
  5. The organization lacks analytics translators
  6. Analytics capabilities are isolated from the business, resulting in an ineffective analytics organization structure
  7. Costly data-cleansing efforts are started en masse
  8. Analytics platforms aren’t built to purpose
  9. Nobody knows the quantitative impact that analytics is providing
  10. No one is hyperfocused on identifying potential ethical, social, and regulatory implications of analytics initiatives

Time will tell about the real value of AI!

Great ADR Program in Palo Alto Sponsored by the SVAMC!

I am honored to be a member of the Silicon Valley Arbitration and Mediation Center Tech-List who was one of the program sponsors, …and it was a great privilege to serve on a Panel about Arbitrating Technology and Patent disputes with Bryan Sinclair from Cisco, Adam Rattray from WIPO, and David Allgeyer at Allgeyer Law & ADR LLC.  The half day program on November 7, 2018 was entitled “Advanced Issues in Tech and Patent ADR: Mediating and Arbitrating Disputes” and co-sponsored by SVAMC, WIPO, Farella Braun & Martel LLP, Wilson Sonsini Goodrich & Rosati.  It was also great to see old friends and meet new friends!

Artificial Intelligence Update: Harvard now offering free access to 6.5 million US law cases!

Harvard announced that “The Library Innovation Lab at the Harvard Law School Library has completed its Caselaw Access Project, an endeavour to digitize every reported state and federal US legal case from the 1600s to last summer.” The announcement entitled “Harvard just put more than 6 million court cases online to give legal AI a boost” included these details “Between 2013 and 2018, the Library digitized over 40 million pages of U.S. court decisions” to help AI, and explained the following:

Why is this needed? One of the biggest hurdles to developing artificial intelligence for legal applications is the lack of access to data. To train their software, legal AI companies have often had to build their own databases by scraping whatever websites have made information public and making deals with companies for access to their private legal files.

What it means: Now that millions of cases are online for free, a good training source will be easily available. Programs will also be able to more easily search case text to provide lawyers with relevant background research for cases.

This is wonderful news for AI!

Court rules that bank had duty to provide banking services to cryptocurrency exchange! reported that a court ruled that the South Korean commercial bank Nonghyup could not terminate a contract even though Nonghyup was trying to comply with “…the anti-money laundering guidelines issued by the regulator Financial Services Commission (FSC).” The November 3, 2018 article entitled “South Korean Court Rules Bank’s Action to End Banking Services to Crypto Exchange Illegal” included these comments:

A court in South Korea has ruled that the decision by a commercial bank to stop offering banking services to a cryptocurrency exchange was unlawful and must therefore be rescinded.

At the beginning of the year, commercial banks providing banking services to cryptocurrency exchanges in the Asian country came under increased scrutiny from regulators intent on cracking down on speculative trading and money laundering and Nonghyup featured prominently among the six banks that were set to be investigated.

Three months later Nonghyup was also among three banks that the Financial Services Commission and the Korea Financial Intelligence Unit indicated would undergo on-site inspections with regards to the services they offered cryptocurrency exchanges.

Just like in the earlier investigation, this one was being conducted to ensure that the financial institutions were adhering to the Know-Your-Client and Anti-Money Laundering rules.

This case will be interesting to follow.

Artificial Intelligence now being used to predict the Next Big Earthquake!

The New York Times reported that “with the help of artificial intelligence, a growing number of scientists say changes in the way they can analyze massive amounts of seismic data can help them better understand earthquakes, anticipate how they will behave, and provide quicker and more accurate early warnings.”  The October 26, 2018 article entitled “A.I. Is Helping Scientists Predict When and Where the Next Big Earthquake Will Be” included these comments:

The new A.I.-related earthquake research is leaning on neural networks, the same technology that has accelerated the progress of everything from talking digital assistants to driverless cars.

Loosely modeled on the web of neurons in the human brain, a neural network is a complex mathematical system that can learn tasks on its own.

Scientists say seismic data is remarkably similar to the audio data that companies like Google and Amazon use in training neural networks to recognize spoken commands on coffee-table digital assistants like Alexa.

When studying earthquakes, it is the computer looking for patterns in mountains of data rather than relying on the weary eyes of a scientist.

Not everyone agrees including Philip Stark (an associate dean at the University of California, Berkeley, at the Division of Mathematical and Physical Sciences) who:

… describes the overall system of earthquake probabilities as “somewhere between meaningless and misleading” and has called for it to be scrapped.

What do you think?