The Korean Intellectual Property Office (KIPO) announced Patent Examination Guidelines for key technology areas related to the Fourth Industrial Revolution, including machine learning based artificial intelligence ("AI"), on January 18, 2021. In the Examination Guidelines for AI, KIPO outlines specific guidelines on description and novelty/inventiveness requirements for different categories of AI inventions (e.g., AI model training invention and AI application invention, as depicted below), in addition to eligibility requirements which correspond to that of computer-related inventions. In particular, KIPO's Examination Guidelines provide examples of various AI inventions with practical drafting tips on enablement (Article 42(3)(i) of Patent Act) and inventiveness requirements (Article 29(2)). Under Article 42(3)(i), the description of an invention shall be written clearly and fully so that a person with ordinary skill in the art (POSITA) to which the invention pertains can easily practice the claimed invention. For an AI invention, KIPO suggests that the description of the technical problem, solution, and specific technical configuration (e.g., training data, data preprocessing, trained model, and loss function, etc.) be included to enable a POSITA to practice the claimed invention, unless the technical configuration is well known in the art.
Say you're a job-seeker who's got a pretty good idea of what employers want to hear. Like many companies these days, your potential new workplace will give you a personality test as part of the hiring process. You plan to give answers that show you're enthusiastic, a hard worker and a real people person. Then they put you on camera while you take the test verbally, and you frown slightly during one of your answers, and their facial-analysis program decides you're "difficult." This is just one of many problems with the increasing use of artificial intelligence in hiring, contends the new documentary "Persona: The Dark Truth Behind Personality Tests," premiering Thursday on HBO Max. The film, from director Tim Travers Hawkins, begins with the origins of the Myers-Briggs Type Indicator personality test.
Artificial intelligence (AI) is considered one of the most revolutionary developments in human history, and the world has already witnessed its transformative capabilities. Not surprisingly, AI-based innovations are powering some of the most cutting-edge solutions we use in our daily lives. Today, AI empowers organizations, governments and communities to build a high-performing ecosystem to serve the entire world. Its profound impact on human lives is solving some of the most critical challenges faced by society. Here are a few innovations for social causes that I find most notable.
The reason for focusing on this area of bias is regarded as important by some enterprises. This is because unconscious bias is often easy to miss. Moreover, unconscious bias is often seen to be far more pervasive in the workplace than blatant discrimination. According to some researchers, unconscious bias can be blamed for lower wages, less opportunities for advancement and high turnover. Unconscious biases are types of social stereotypes held by members of one group about other groups of people.
An academic and a lawyer have teamed up to develop a robot lawyer, which, if successful, will make legal advice affordable to people from all backgrounds, while revolutionising the legal sector. Robots could take on significant parts of a lawyer's work, reducing the costs and barriers to access to legal services for everyone, rather than just those who can afford the high costs. The project, at the University of Bradford, is initially working on a machine learning-based application to provide immigration-related legal advice, but if successful, it could be replicated across the legal sector. The idea has received government backing in the form of a £170,000 grant from Innovate UK Knowledge Transfer Partnerships. Legal firm AY&J Solicitors is providing a further £70,000 as well as the vital knowledge of lawyers.
Artificial intelligence is becoming good at many "human" jobs--diagnosing disease, translating languages, providing customer service--and it's improving fast. This is raising reasonable fears that AI will ultimately replace human workers throughout the economy. Never before have digital tools been so responsive to us, nor we to our tools. While AI will radically alter how work gets done and who does it, the technology's larger impact will be in complementing and augmenting human capabilities, not replacing them. Certainly, many companies have used AI to automate processes, but those that deploy it mainly to displace employees will see only short-term productivity gains. In our research involving 1,500 companies, we found that firms achieve the most significant performance improvements when humans and machines work together. Through such collaborative intelligence, humans and AI actively enhance each other's complementary strengths: the leadership, teamwork, creativity, and social skills of the former, and the speed, scalability, and quantitative capabilities of the latter. What comes naturally to people (making a joke, for example) can be tricky for machines, and what's straightforward for machines (analyzing gigabytes of data) remains virtually impossible for humans.
We've seen widespread disruption, change and uncertainty in every sphere of business. Yet, chaotic, unstable times tend to also bring great leaps forward in terms of technology and innovation. In 2020, I've seen numerous enterprises discover just how much AI and ML tools can help their organization remain stable and even continue to grow despite the turmoil rolling through the markets. But this growth comes with the necessity to assure the health of ML models in production to avoid drifts, biases and anomalies. While AI adoption has taken a giant leap forward, we've learned that ML models need to be adaptable and robust.
I recently read an article about ageism, and how companies are struggling to effectively manage it. A short time later I read about Artificial Intelligence (AI), and how it will make Talent Acquisition (TA) more efficient. So, I started thinking…how will AI and ageism coexist? Bias is practiced every day by everyone, starting with personal preference for morning coffee and what goes in it, to our taste in cars (Tesla), to what to buy on Amazon, and more. We also have strong biases in technology preference: Mac or PC, iPhone or Galaxy, Samsung, or LG?
In May 2015, The Simpsons voice actor Harry Shearer – who plays a number of key characters including, quite incredibly, both Mr Burns and Waylon Smithers – announced that he was leaving the show. By then, the animated series had been running for more than 25 years, and the pay of its vocal cast had risen from $30,000 an episode in 1998 to $400,000 an episode from 2008 onwards. But Fox, the producer of The Simpsons, was looking to cut costs – and was threatening to cancel the series unless the voice actors took a 30 per cent pay cut. Most of them agreed, but Shearer (who had been critical of the show's declining quality) refused to sign – after more than two decades, he wanted to break out of the golden handcuffs, and win back the freedom and the time to pursue his own work. Showrunner Al Jean said Shearer's iconic characters – who also include Principal Skinner, Ned Flanders and Otto Mann – would be recast.
That the regulation of Artificial intelligence is a hot topic is hardly surprising. AI is being adopted at speed, news reports frequently appear about high-profile AI decision-making, and the sheer volume of guidance and regulatory proposals for interested parties to digest can seem challenging. What can we expect in terms of future regulation? And what might compliance with "ethical" AI entail? High-level ethical AI principles were made by the OECD, EU and G20 in 2019.