This is the sixth, and final episode in a series dedicated to all things A.I. In this episode, Tae Royle, Head of Digital Products APAC from Ashurst Advance Digital is joined by Tara Waters, Partner and Head of Ashurst Advance Digital. This is the sixth and final episode in a series dedicated to all things Artificial Intelligence. My name is Tae Royle head of digital products from Ashurst did that digital and today I'm joined by Tara Waters partner and head of Ashurst Advanced Digital based out of our London office. Naturally we come to the question of what's next? In Lewis Carroll's second novel, Alice enters Wonderland by climbing through a mirror.
But what happens when artificial intelligence is biased? What if it makes mistakes on important decisions -- from who gets a job interview or a mortgage to who gets arrested and how much time they ultimately serve for a crime? "These everyday decisions can greatly affect the trajectories of our lives and increasingly, they're being made not by people, but by machines," said UC Davis computer science professor Ian Davidson. A growing body of research, including Davidson's, indicates that bias in artificial intelligence can lead to biased outcomes, especially for minority populations and women. Facial recognition technologies, for example, have come under increasing scrutiny because they've been shown to better detect white faces than they do the faces of people with darker skin.
As technology improves, AI and ML applications are becoming increasingly pivotal for businesses to stay ahead of their competition. The time will soon come when a business that doesn't leverage AI in its decision making processes will find itself out in the cold. While AI holds a lot of potential, the technology is still nascent and prone to error. A big reason for this is the so-called "cold start" problem. ML algorithms rely on historical data being fed to them, so they can learn and get better and better at predicting future data patterns.
Legal scholars have in the last several years embarked upon an ongoing discussion and debate over a potential Legal Singularity that might someday occur, involving a variant or law-domain offshoot leveraged from the Artificial Intelligence (AI) realm amid its many decades of deliberations about an overarching and generalized technological singularity (referred to classically as The Singularity). This paper examines the postulated Legal Singularity and proffers that such AI and Law cogitations can be enriched by these three facets addressed herein: (1) dovetail additionally salient considerations of The Singularity into the Legal Singularity, (2) make use of an in-depth and innovative multidimensional parametric analysis of the Legal Singularity as posited in this paper, and (3) align and unify the Legal Singularity with the Levels of Autonomy (LoA) associated with AI Legal Reasoning (AILR) as propounded in this paper.
They were responding to the famed futurist's prediction at the COSM 2019 Technology Summit that we will merge with our computers by 2045--The Singularity. "Our intelligence will then be a combination of our biological and non-biological intelligence," he explained. We will then be apps of our smart computers. Kurzweil, a Director of Engineering at Google, should be taken seriously. He boasts a 30-year track record of accurate predictions and many key patents.
What if I told a story here, how would that story start?" Thus, the summarization prompt: "My second grader asked me what this passage means: …" When a given prompt isn't working and GPT-3 keeps pivoting into other modes of completion, that may mean that one hasn't constrained it enough by imitating a correct output, and one needs to go further; writing the first few words or sentence of the target output may be necessary.
Artificial intelligence AI takes the lead over intelligent automation IA. Intelligent automation is the combination of "'robotic process automation and artificial intelligence to automate processes,'" according to a recent article on the topic in HR Dive, a publication for human resources professionals. Organizations that embrace intelligent automation may experience a return on investment of 200% or more, according to an Everest Group report cited by HR Dive. However, that doesn't mean organizations can expect a reduction in headcount, according to the report. In fact, projections of a reduction in workforce thanks to intelligent automation may be "highly exaggerated," the Everest Group noted.
Every day organisations face risks to their security and business continuity. These may include industrial espionage, cyber attacks, protests, union strikes, terrorism, epidemic, natural disasters and the list is endless. Keeping track on all the events potentially hampering business operations and the security of employees and assets is not an easy task, and it all starts with collecting the right information via "threat intelligence". Threat intelligence is the process of collecting and elaborating information on existing or emerging risks or hazard to people, assets or operations, with the purpose of informing decision makers and, whenever possible, preventing or mitigating operational or strategic threats if and when they occur. Since most of the information is collected via openly available media and social media (so called Open Source Intelligence or OSINT), practitioners and threat intelligence solution providers have been looking at Artificial Intelligence (AI) to find more relevant information faster.
America's intelligence collectors are already using AI in ways big and small, to scan the news for dangerous developments, send alerts to ships about rapidly changing conditions, and speed up the NSA's regulatory compliance efforts. But before the IC can use AI to its full potential, it must be hardened against attack. The humans who use it -- analysts, policy-makers and leaders -- must better understand how advanced AI systems reach their conclusions. Dean Souleles is working to put AI into practice at different points across the U.S. intelligence community, in line with the ODNI's year-old strategy. The chief technology advisor to the principal deputy to the Director of National Intelligence wasn't allowed to discuss everything that he's doing, but he could talk about a few examples.