Artificial Intelligence - New Opportunities, Challenges and Limitations

Thoughts and Observations about Artificial Intelligence, Machine Learning, ChatBots, ChatGPT, Generative?Intelligence and more:

“(Artificial Intelligence) AI isn't coming, its here and like brick phones from the 80's the tech is just getting started.”? Mike Wolford – U.S talent acquisition executive, Director of Analytics at Wilson , Contributing Writer at RecruitingDaily .

“ChatGPT and other Generative AI platforms will have huge implications for business productivity.” Hendrith Vanlon Smith Jr, MBA . - U.S. business executive, Managing Partner at Mayflower-Plymouth Capital Capital LLC, author of “Business Essentials”.

“It is difficult to think of a major industry that AI will not transform. This includes healthcare, education, transportation, retail, communications, and agriculture. There are surprisingly clear paths for AI to make a big difference in all of these industries.” Andrew Ng - British-born/U.S. computer scientist & technology entrepreneur focusing on machine learning and AI, was a co-founder and head of Google Brain and was chief scientist at 百度 , building the company's Artificial Intelligence Group, Co-Founder and Chairman of Coursera , General Partner of the AI Fund , Founder of DeepLearning.AI , Founder & CEO of LandingAI .

“Forecasters at 普华永道 (PricewaterhouseCoopers) predict that AI could boost the global economy by over $15 trillion by 2030.” Reported by Andrew R. Chow and Billy Perrigo - U.S. journalists, posted February 16, 2023 on TIME .

“The race for AI supremacy is on. 微软 , 谷歌 , 百度 and a host of smaller firms are all placing bets on the technology’s future. Which version emerges on top may well determine how people find information online for decades to come.” From The Economist Podcast “I Use Advanced Machine Learning To Generate Answers From The Mouths Of Bots”.

“In December of last year (2022), OpenAI, a startup artificial intelligence company based in San Francisco, created a chatbot. This isn’t just any chatbot like the ones we frequently encounter when browsing the internet; this chatbot has humanoid-like responses. The chatbot is called ChatGPT, and it’s able to carry out complex conversations with humans.?The reason why the chatbot is capable of doing such things is because it’s trained using RLHF, also known as reinforcement learning from human feedback. RLHF involves human AI trainers, and in turn, it’s able to generate responses to text inputs made by users.” Posted by Jenina Mallari - U.S. writer, on February 9, 2023 on the Los Angeles Weekly.

“If you’re wondering how to trade the AI craze spurred by ChatGPT, researchers at Baird (Robert W. Baird & Co.) say they have you covered. ‘Companies in our list have advanced AI capabilities, and we believe will be beneficiaries of the 'tidal wave' of AI-powered applications,’ Colin Sebastian , senior research analyst at Baird, and his team wrote in a note to investors. … The list, compiled by senior research analyst Mark Marcon, CFA , includes the following highlights: ? Workday (WDAY) ‘WDAY has always been a leader in AI/ML [artificial intelligence/machine learning], being one of the first software companies to heavily emphasize and invest in it,’ wrote Marcon. ‘During the last investor day, WDAY emphasized that ML is being incorporated into every element of the platform.’ The analyst also highlights the human resource company’s relationships with Microsoft and Google who are both leaders in AI/ML. ?AUTOMATIC DATA PROCESSING ( ADP ) The payroll company began discussing its interest in artificial intelligence and machine learning several years ago as a way to leverage its data to add value to clients. ‘Data is one of the most important inputs for developing and maintaining a successful AI/ML program, and ADP and PAYX have the most data out of any payroll provider, paying a collective one in four private sector payrolls in the U.S,’ wrote Marcon. Robert Half (RHI) The staffing company already has the most robust AI/ML capabilities out of its public peers. ‘RHI has a proprietary database of over 30mn candidates, and RHI uses AI/ML to find the best matched candidates to open positions, materially improving recruiter productivity,’ wrote Marcon. ‘Further opportunities include using AI/ML and chatbots for candidate and client outreach, potentially reducing both service and sales costs,’ he added. Marcon added one negative note for all staffing and recruiting organizations: Some of the positions filled by these companies ‘at some point in the future could be automated away by AI/ML-enabled software. Many staffing companies are moving up the value chain to reduce their exposure to positions that can be displaced through automation,’ wrote the analyst.” ?Report by Ines Ferre - U.S. journalist, Senior Business Reporter for Yahoo Finance , posted on February 21, 2023.

“Artificial Intelligence is a range of analytical techniques that allows a computer to detect relationships, predict outcomes, and often act based on the patterns in data without being explicitly programmed to do so.” 贝恩公司

“Generative artificial intelligence is in the zeitgeist. It’s the culmination of years of development in machine learning algorithms, advancements in AI-focused computer chips, and familiar user interfaces that actually allow nontechnical people to access these new frontiers. Lauren Goode – U.S. journalist, senior writer at WIRED covering consumer tech issues.

“Throughout the business world, every company these days is basically in the data business and they’re going to need AI to civilize and digest big data and make sense out of it—big data without AI is a big headache.”?Kevin Kelly – U.S. co-founder of WIRED Magazine, former editor/publisher of the Whole Earth Review .

“Generative AI, of which ChatGPT is an example, wades through oceans of data to conjure up original content - an image, a poem, a thousand-word essay - in seconds and upon a simple request. Since its discrete release in late November (2022), ChatGPT has become one of the fastest growing apps ever and pushed Microsoft and Google to rush out projects that had until now stayed carefully guarded over fears that the technology wasn't yet ready for the public. ‘Just five days after its release, a million people used ChatGPT - about 60 times faster than it took Facebook to reach one million users,’ said Wayne Hu , a partner at (venture capital firm) SignalFire . Posted on February 19, 2023 on The Economic Times .

“The platforms are based on what are called large language models (LLMs) or sometimes generative language models or transformer language models — the GPT in ChatGPT stands for "generative pretrained transformer." These are machine learning systems that process terabytes' worth of data, often just scraped directly from the internet, making note of patterns and associations within the dataset, which is called training data.?In the case of ChatGPT, text data sets are enough. Image generators like Dall-E, Stable Diffusion and Midjourney are trained by looking at a wealth of images and learning what they are by reading captions that accompany them, so the models still rely on language. A neural network is a type of machine learning system that can be trained on tons of data and can then spit out insights from the patterns. Such a neural net isn't new. What's happening with publicly available generative systems that have debuted in the past year is that these patterns are not only learning, they're also then paired with a second neural network that reverse engineers the process to create content and checks it against the first neural net to make sure it matches the prompt given to the system.?In essence, you give ChatGPT or Dall-E a prompt and they formulate a response by predicting what the next word (or pixel in the case of an image) should be based on all the patterns and associations gleaned from training data.” Eric Mack – U.S. journalist, posted on CNET on February 18, 2023.

“A neural network is just a mathematical system that learns skills by analyzing vast amounts of digital data. As a neural network examines thousands of cat photos, for instance, it can learn to recognize a cat. Most people use neural networks every day. It’s the technology that identifies people, pets and other objects in images posted to internet services like Google Photos. It allows Siri and Alexa, the talking voice assistants from 苹果 and 亚马逊 , to recognize the words you speak. And it’s what translates between English and Spanish on services like Google Translate. Neural networks are very good at mimicking the way humans use language. And that can mislead us into thinking the technology is more powerful than it really is. How exactly do neural networks mimic human language? About five years ago, researchers at companies like 谷歌 and OpenAI , a San Francisco start-up that recently released the popular ChatGPT chatbot, began building neural networks that learned from enormous amounts of digital text, including books, Wikipedia articles, chat logs and all sorts of other stuff posted to the internet. These neural networks are known as large language models. They are able to use those mounds of data to build what you might call a mathematical map of human language. Using this map, the neural networks can perform many different tasks, like writing their own tweets, composing speeches, generating computer programs and, yes, having a conversation.” Reported by Cade Metz – U.S. journalist, technology reporter, posted on February 16, 2023, on 纽约时报 .

“Every serious technology company now has an Artificial Intelligence team in place. These companies are investing millions into intelligent systems for situation assessment, prediction analysis, learning-based recognition systems, conversational interfaces, and recommendation engines. Companies such as Google, Facebook, and Amazon aren’t just employing AI, but have made it a central part of their core intellectual property.”? Kristian Hammond – U.S. professor of Computer Science and Journalism at 美国西北大学 , Chief Scientist at Narrative Science, company focused on automated narrative generation from data.

“In the last few months, artificial intelligence (AI) has garnered much attention, especially with the arrival of ChatGPT. The program … has amazed people with its ability to answer questions and write stories while mimicking natural speech. In the progression of AI, many see ChatGPT as a big step. But as these new technologies increase, they are likely to raise questions. AI has long been a curiosity — and a fear — straight out of science fiction books and films, from the Hal 9000 to M3gan.?In more ways than one, though, ChatGPT seems to have changed the game, starting with how quickly it garnered an audience. ChatGPT launched on November 30, 2022. By the end of January (2023), it had more than 100 million monthly users, according to a report from UBS. That made it the fastest-growing consumer application in history. The next fastest application to reach the 100 million mark was TikTok, which took nine months to get there.?Instagram took 30 months to hit that mark, and Spotify took 55 months.” Posted on NBC News on February 19, 2023 by Dante Chinni , U.S. journalist specializing in data analysis, politics and culture, created Patchwork Nation, directs the American Communities Project , which is based at 美国密歇根州立大学 .

“…?In the months since its debut, ChatGPT … has become a global phenomenon. Millions of people have used it to write poetry, build apps and conduct makeshift therapy sessions. It has been embraced (with mixed results) by news publishers, marketing firms and business leaders. And it has set off a feeding frenzy of investors trying to get in on the next wave of the A.I. boom. … But two months after its debut, ChatGPT has more than 30 million users and gets roughly five million visits a day, two people with knowledge of the figures said. That makes it one of the fastest-growing software products in memory. (Instagram, by contrast, took nearly a year to get its first 10 million users.) The growth has brought challenges. ChatGPT has had frequent outages as it runs out of processing power, and users have found ways around some of the bot’s safety features. The hype surrounding ChatGPT has also annoyed some rivals at bigger tech firms, who have pointed out that its underlying technology isn’t, strictly speaking, all that new. …. Despite its limitations, ChatGPT’s success has vaulted OpenAI into the ranks of Silicon Valley power players. … The race is heating up. 百度 , the Chinese tech giant, is preparing to introduce a chatbot similar to ChatGPT in March, according to Reuters. Anthropic , an A.I. company started by former OpenAI employees, is reportedly in talks to raise $300 million in new funding. And 谷歌 is racing ahead with more than a dozen A.I. tools. Then there’s GPT-4, which is still scheduled to come out this year. When it does, its abilities may make ChatGPT look quaint. Or maybe, now that we’re adjusting to a powerful new A.I. tool in our midst, the next one won’t seem so shocking.” Kevin Roose – U.S. journalist, ?technology columnist, posted February 3, 2023 on 纽约时报 .

“Our ultimate objective is to make programs that learn from their experience as effectively as humans do. … The study is to proceed on the basis of the conjecture that every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it. An attempt will be made to find how to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves. … We shall…say that a program has common sense if it automatically deduces for itself a sufficient wide class of immediate consequences of anything it is told and what it already knows.” John McCarthy –U.S. computer scientist, cognitive scientist, one of the founders of artificial intelligence.

“AI’s computational power is doubling every six to 10 months, researchers say. It is exactly this immense power that makes the current moment so electrifying-and so dangerous.” Reported by Andrew R. Chow and Billy Perrigo – U.S. journalists, posted February 16, 2023 on TIME .

“A century ago, we had essentially no way to start to explain how thinking works. Then psychologists like Sigmund Freud and Jean Piaget produced their theories about child development. Somewhat later, on the mechanical side, mathematicians like Kurt G?del and Alan Turing began to reveal the hitherto unknown range of what machines could be made to do. These two streams of thought began to merge only in the 1940s, when Warren McCulloch and Walter Pitts began to show how machines might be made to see, reason, and remember. Research in the modern science of Artificial Intelligence started only in the 1950's, stimulated by the invention of modern computers. This inspired a flood of new ideas about how machines could do what only minds had done previously.”?Marvin Minsky –U.S. cognitive and computer scientist, focused on research of artificial intelligence, co-founder of the? 美国麻省理工学院 ’s AI laboratory.

"I think [practical AI use] is here and now. We do have a shortage of labor in the real world and that's because of a demographic issue that the world is facing... the United States is now sitting at 3.4% unemployment, the lowest in 60 years. So maybe we can find tools that replace some portions of labor, and it's a good thing this time. A big chunk of (regulatory work in health care and finance) could get automated using these techniques.”?… (Further out) AI will likely be capable of managing "things in like drug discovery or in trying to finish up chemistry". As for human resources … the tech could do 90% of data processing needed for "promoting people, hiring people, moving people" while the final judgement calls are still left in human hands. Arvind Krishna - Indian-U.S. business executive CEO of IBM , posted on Fortune on February 16, 2023.

“Machine learning and artificial intelligence are the keys to just about every aspect of life in the very near future: every sector, every business. If you run a business, its future depends on your ability to generate data about its activities, data that can then be fed into algorithms.” Enrique Dans - Spanish Professor of Innovation at IE Business School .

“Dig into every industry, and you'll find AI changing the nature of work.”? Daniela Rus ?- Romanian-U.S. roboticist,?Director of the? MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) , Andrew and Erna Viterbi Professor in the Department of Electrical Engineering and Computer Science at the 美国麻省理工学院 .?

“AI will take many single-task, single-domain jobs away. You can argue that humans have abilities that AI does not: We can conceptualize, strategize, create. Whereas today's AI is just a really smart pattern recognizer that can take in data [and] optimize. But how many jobs in the world are simple repetitions of tasks that can be optimized?”?Kai -Fu Lee - Taiwanese computer scientist, businessman, writer, developed a speaker-independent, continuous speech recognition system as his Ph.D. thesis at? 美国卡内基梅隆大学 , later worked as an executive at? 苹果 , SGI, 微软 , and 谷歌 . Currently based in Beijing, China.

“It's true that the upheaval brought by the arrival of AI will initially disrupt existing employment patterns as roles are redefined and shared between man and machine. On the flip side there is the potential for job creation and enterprise opportunities, brought about by the displacement of mundane and repetitive work, freeing up valuable time and creativity applicable to roles higher up the value chain -- jobs where people, rather than machines, are essential.” Ben Rossi – U.S. AI Researcher at Two Sigma ?Investments.

“…the increasing prominence of AI has implications for every corner of the economy… FARMING - Monitoring weather patterns, managing pests and disease, working out the need for extra irrigation, or even which crops to grow where: many farmers believe agriculture is fertile ground for artificial intelligence. … AI’s capacity for combining and analyzing large datasets is already supplying farmers with real-time information on how to improve the health of their crops and increase yields. Drones and in-ground sensors can play a role in observing growing crops and soil conditions across hundreds of acres of land, including checking whether they need more water, fertilizer or herbicide and whether they are being affected by disease or destroyed by animals. NEWS MEDIA - Media companies have embraced machine learning to boost subscriptions and advertising and to help make decisions about what stories to promote. … News organizations are hiring data scientists on six-figure salaries to pull together data to track customers and guide them towards particular products, while also providing workers with tools to take the grunt work out of finding and writing stories. Energy - With tight margins in a sector where almost 30 companies have gone bust during the energy crisis, retail energy suppliers are expected to increase the use of AI to cut down call times. Chatbots are used to ask basic questions before customers speak to a human adviser. Ultimately, suppliers envisage AI will play a central role in future “smart grids”, allowing supply and demand to be more closely aligned, with a new generation of devices from smart meters and electric vehicles to solar panels and heat pumps able to improve efficiency. MANUFACTURING - Machine learning algorithms are already being deployed on the burgeoning piles of data produced within big factories for ‘predictive maintenance’ – replacing parts before they fail and potentially requiring fewer technicians. But the rapid rise of generative artificial intelligence suggests it will not only be people on factory lines who will be affected. Generative AI is already being used to design products much more quickly, test them virtually as a ‘digital twin’, and manufacture them much more quickly. Combined with innovations such as 3D printing, this could lower development costs dramatically and would require fewer engineers in aerospace, automotive and consumer electronics. One logical end is something like the Star Trek replicator, a bot that designs and makes whatever its user desires from a text prompt – without human involvement.?GOVERNMENT - Running the country means the government collects vast amounts of personal and business data, all of which could be plugged into artificial intelligence and machine learning systems to improve the efficiency of policymaking and delivery of services. Everything from bin collections, call centers and analysis of data to prioritize spending could be targeted for improvement. TRANSPORT – London (transport service) uses AI to help traffic flow and forecast disruption, while train operators have used simulators or digital twins to check train paths, platforms and timetables. The Rail Safety and Standards Board is working with academics to use machine learning from high-resolution video to tackle leaves on the line. Similar AI and video projects in Australia could teach driverless trains to recognize a green light – or whether the movement on a remote track is an encroaching human or a nearby kangaroo. FINANCIAL SERVICES - The financial services sector is at greater risk of job losses from AI than other sectors, according to government forecasts, but experts say this is partly a matter of catch-up. ‘Other industries have already made these cuts,’ said Sarah Kocianski, an independent fintech consultant. … (B)anks and wealth managers will need fewer staff to onboard new clients as they automate more of their customer background checks and will rely more heavily on AI to detect and flag potential fraud and money-laundering risks. They will also be able to feed new guidelines from regulators into those machine learning programs, to flag any potential breaches or shortfalls in the company’s systems, rather than relying on humans to conduct an initial review. But these systems will still require human oversight, not only to build and program the technology but also to conduct additional checks and sort out more complex problems. RETAIL - Almost a third of retail jobs could be displaced by technology by 2030 compared with 2017 levels, (due to) automated tills, warehouse robotics and AI-based planning tools. … The most obvious change to any shopper is the rise in the use of self-checkouts and self-scanning systems in supermarkets in the last five years. Change was supercharged by the pandemic when labor became more expensive and difficult to find while shoppers became wary of interactions with staff. Analysts at the advisory firm McKinsey have predicted that the number of cashiers could almost halve between 2017 and 2030 as these technologies are rolled out. Electronic labels on shelves, so prices can be changed automatically from head office, alongside AI-led technology to guide buying decisions and more robotics to pick and pack products in warehouses will also affect thousands of jobs.” Posted on February 18, 2023, on The Guardian . Reported by Joanna Partridge , Jane Barrett , Alex Lawson, Jasper Jolly , Richard Partington , GwynTopham, Kalyeena Makortoff and Sarah Butler – U.K. journalists.

“Technology is going to disrupt the future of work, perhaps sooner than we thought. We are exploring everything from AI to VR, but we see no substitute to our stores and our employees. We focus on building talent and personal service.” Brian Cornell - U.S. businessman, chairman and chief executive officer of the 塔吉特百货 Corporation, also non-executive chairman of 百胜集团 .

“Today’s smart retailer is engaging in a new era of shopping experience, combining the human touch and technology to deliver a more tailored consumer experience.” Guita Blake - U.K. Global Tech-Digital consultant, formerly VP of Mindtree .

“AI is an engine that is poised to drive the future of retail to all-new destinations. The key to success is the ability to extract meaning from big data to solve problems and increase productivity.” Azadeh Yazdan - U.S Electrical Engineer-Business Executive - Director of Business Development, AI Products Group - Meta Facebook .

“More and more brands are harnessing the power of AI to implement tailored product recommendations, and are seeing results. It’s estimated that 35% of Amazon’s sales come from its recommended products feature.”? Meghann York -U..S Business Executive- Global Head of Product Marketing, Marketing Solutions at SAP .

“Firms will address the pragmatic side of AI now that they have a better understanding of the challenges and embrace the idea that ‘no pain means no AI gain.’ The AI reality is here. Firms are starting to recognize what it is and isn’t…and they are seeing the real challenges of AI versus what they assumed the challenges would be.” Michele Goetz – U.S. Business Analyst, Vice President/Principal Analyst at Forrester .

“It’s natural to wonder if there will be a jobless future or not. What we’ve concluded, based on much research, is that there will be jobs lost, but also gained, and changed. The number of jobs gained and changed is going to be a much larger number, so if you ask me if I worry about a jobless future, I actually don’t. That’s the least of my worries.” James Manyika – Zimbabwean-U.S. technology consultant, researcher, author, currently Senior Vice President, Technology and Society at 谷歌 - Alphabet Inc. , previously Senior Partner at 麦肯锡 , and Chairman and Director at McKinsey Global Institute (MGI). Known for his research in artificial intelligence, robotics automation, and the future of work.

“Humans need and want more time to interact with each other. I think AI coming about and replacing routine jobs is pushing us to do what we should be doing anyway: the creation of more humanistic service jobs.” Kai-Fu Lee- Taiwanese computer scientist, businessman, writer.

“We’re going to see tremendous occupational shifts. Some jobs will climb while others decline. So how do we enable and support workers as they transition from occupation to occupation? We don’t do that very well. I worry about the skill shifts. Skill requirements are going to be substantial and how do we get there quickly enough?” James Manyika - Zimbabwean-U.S. consultant, Senior Vice President of Technology and Society at 谷歌 - Alphabet Inc.

“As important as it is to educate the new sets of generations coming in, I also think it’s important to educate the existing workforce, so they can understand how to have AI serve them and their roles.” Sarah Aerni – U.S. IT executive, Senior Director AI/Machine Learning and Engineering at Salesforce .

“Intelligent automation can be an important asset in digital transformation, particularly as global enterprises adapt to a new reality of distributed work.” Mihir Shukla - U.S. entrepreneur, CEO and Co-founder - Automation Anywhere , dedicated to Robotics Process Automation - digital workforce, and intelligent automation.

“The AI of the past used brute-force computing to analyze data and present them in a way that seemed human. The programmer supplied the intelligence in the form of decision trees and algorithms. Imagine that you were trying to build a machine that could play tic-tac-toe. You would give it specific rules on what move to make, and it would follow them. Today's AI uses machine learning in which you give it examples of previous games and let it learn from the examples. The computer is taught what to learn and how to learn and makes its decisions. What's more, the new AIs are modeling the human mind itself using techniques similar to our learning processes.”? Vivek Wadhwa – U.S. tech entrepreneur, professor at 美国卡内基梅隆大学 , author.

“Nowadays, we have computers performing tasks that require the equivalent of human intelligence. Back in the day it was thought that this would require a certain type of processing: a deep semantic representation of meaning and complex inference. It turns out that sheer brute force data analytics cuts the mustard just as well.” Alan Smeaton – Irish researcher, professor at Dublin City University , founding director at Insight Research Ireland Centre for Data Analytics .

“Artificial intelligence is based on the assumption that the mind can be described as some kind of formal system manipulating symbols that stand for things in the world. Thus it doesn’t matter what the brain is made of, or what it uses for tokens in the great game of thinking. Using an equivalent set of tokens and rules, we can do thinking with a digital computer, just as we can play chess using cups, salt and pepper shakers, knives, forks, and spoons. Using the right software, one system (the mind) can be mapped onto the other (the computer).” George Johnson – U.S. science writer, 纽约时报 , co-hosts (with science writer John Horgan) weekly series "Science Faction" on Bloggingheads.tv.

“… this technology (and there are many others like it) is what is often called a “language machine” that uses statistics, reinforcement learning, and supervised learning to index words, phrases, and sentences. While it has no real “intelligence” (it doesn’t know what a word “means” but it knows how it is used), it can very effectively answer questions, write articles, summarize information, and more. Engines like ChatGPT are “trained” (programmed and reinforced) to mimic writing styles, avoid certain types of conversations, and learn from your questions. In other words, the more advanced models can refine answers as you ask more questions, and then store what it learned for others. While this is not a new idea (we’ve had chatbots for a decade, including Siri, Alexa, Olivia, and more), the level of performance in GPT-3.5 (the latest version) is astounding. I’ve asked it questions like “what are the best practices for recruiting?” or “how do you build a corporate training program?” and it answered pretty well. Yes, the answers were quite elementary and somewhat incorrect, but with training, they will clearly get better. … In some ways the chatbot itself may be a commodity: There are at least 20 startups with highly funded AI teams building derivative or competing products.” Josh Bersin – U.S. HR analyst, posted on January 24, 2023 on HR Executive.

“While artificial intelligence might seem more like sci-fi than reality, the technology is catching up to the hype. Many organizations are turning to automation to streamline the hiring process and relieve recruiters of time-consuming, tedious, and repetitive tasks.” Jobvite - U.S. Software Applicant Tracking System Company

“… artificial intelligence is already streamlining recruitment, onboarding, training, and ongoing staff analytics processes. … In general terms, AI can be defined as a technology capable of making decisions independently from humans without the need for direct instruction. In other words, machines can autonomously learn from their surroundings and make decisions based on what they have learned. Artificial intelligence (AI) is an area in computer science that emphasizes the creation of intelligent machines. These machines range from agent dialogue systems, autonomous cars, and image recognition software to help desk assistants, virtual personal assistants, and self-driving vehicles. … The first use of AI is in recruitment. This process includes filtering through applicants to find the best matches for open roles based on skillset, experience, competencies, and cultural fit. Machine learning can help HR professionals identify these attributes with better accuracy than traditional sorting methods like resume screenings or telephone screenings. The next area where AI can help is during the onboarding process. Once an applicant has been identified as a good match for an open role, it becomes necessary to bring them into the company and integrate them with existing employees. This is where machine learning can assist by automatically generating personalized emails, scheduling meetings, or even phoning new hires to give them a warm welcome. Finally, AI can assist in coaching employees for better business performance. This is where the real value of machine learning lies because this technology allows for constant feedback loops that are specific to each individual worker. Machine intelligence can assess an employee's strengths and weaknesses based on their own personal data (like location, team members, role, etc.) and give them actionable suggestions for improvement.” Mike Gannon - U.S. HR executive, Chairman and CEO at Turtle Cove Strategic Partners llc , posted on Linkedin on January 25, 2022.

“There has been a lot written about the emergence of ChatGPT and the impact it will have on everything from college term papers to journalism to HR. It’s a fascinating topic that simultaneously fills me with both amazement at the technology and a sense of dread about what it means to the human condition. The reality is that AI is ubiquitous, and it’s powering investment. 微软 recently invested heavily in OpenAI (the group responsible for ChatGPT), with the global AI market projected to reach a value of $1.84 billion by 2030. Meanwhile, Forbes reports that the number of active AI start-ups since 2000 has increased by 14 times, and 72% of executives in a recent 普华永道 survey believe that AI will be the most significant business advantage of the future. It’s reminiscent of the early days of the dot-com era, when everyone scrambled to find ways to both profit from the explosion in technical capabilities and avoid being left behind as their competitors adopted new approaches to work. As someone who works with organizations to transform their business, I see the tremendous opportunities associated with AI. In digital transformations, AI can automate much of the transactional work needed to move historical data and test configurations. It can drive efficiency in business processes through RPA, enabling automation where delivered functionality is not present. Additionally, AI can power Tier 0 support in shared services through chatbots that can answer employees’ basic questions. Unfortunately, in the rush to exploit the benefits of new technology, there is an inherent danger in moving so quickly that you can’t assess risk. And with the legal lag that comes with rapidly emerging technologies, regulation is not equipped to proactively address some of the challenges associated with AI before it does unintentional harm, despite the fact that 81% of tech leaders would like to see more regulation, according to a recent report by DataRobot .” Mary Faulkner – U.S. talent strategist, Principal with IA, prior to joining IA spent nearly 20 years as an HR leader. Posted January 31, 2023 on HR Executive.

“This is just the beginning as AI becomes a new member of the team. And visionary HR leaders will increasingly consider chatbots another co-worker, helping to orient and train them, and assisting the rest of the team in understanding how to work with them. The end result will be more time for employees to do what makes them uniquely human such as: complex problem solving, critical thinking, and creativity, the top three skills deemed essential by the World Economic Forum.” Jeanne C M. -U.S. founding partner of Future Workplace, now part of Executive Networks , an HR Executive Network and Research firm.

“The playing field is poised to become a lot more competitive, and businesses that don’t deploy AI and data to help them innovate in everything they do will be at a disadvantage.” Paul Daugherty -U.S. business executive, Chief Technology and Innovation Officer at? 埃森哲 .

“Harnessing machine learning can be transformational, but for it to be successful, enterprises need leadership from the top. This means understanding that when machine learning changes one part of the business — the product mix, for example — then other parts must also change. This can include everything from marketing and production to supply chain, and even hiring and incentive systems.” Erik Brynjolfsson ?– U.S. author, inventor, Jerry Yang and Akiko Yamazaki Professor and Senior Fellow at? 美国斯坦福大学 directing the Digital Economy Lab.

“Our research says that 50% of the activities that we pay people to do can be automated by adapting currently demonstrated technologies. We think it’ll take decades, but it will happen. So there is a role for business leaders to try to understand how to redeploy talent. It’s important to think about mass redeployment instead of mass unemployment. That’s the right problem to solve.” Michael Chui – U.S. technology consultant, partner at 麦肯锡 , McKinsey Global Institute .

“… artificial intelligence (AI) programs are painting cosmic portraits, responding to emails, preparing tax returns, and recording metal songs. They’re writing pitch decks, debugging code, sketching architectural blueprints, and providing health advice. Artificial intelligence has already had a pervasive impact on our lives. AIs are used to price medicine and houses, assemble cars, determine what ads we see on social media. But generative AI, a category of system that can be prompted to create wholly novel content, is much newer. This shift marks the most important technological breakthrough since social media. Generative AI tools have been adopted ravenously in recent months by a curious, astounded public, thanks to programs like ChatGPT, which responds coherently (but not always accurately) to virtually any query, and Dall-E, which allows you to conjure any image you dream up. In January, ChatGPT reached 100 million monthly users, a faster rate of adoption than Instagram or TikTok . Hundreds of similarly astonishing generative AIs are clamoring for adoption, from Midjourney to Stable Diffusion to GitHub ’s Copilot, which allows you to turn simple instructions into computer code. Proponents believe this is just the beginning: that generative AI will reorient the way we work and engage with the world, unlock creativity and scientific discoveries, and allow humanity to achieve previously unimaginable feats.” Reported by Andrew R. Chow and Billy Perrigo – U.S. journalists, posted February 16, 2023 on TIME .

“Arthur C. Clarke (U.K. science-fiction writer, science writer, futurist, inventor, undersea explorer, co-wrote the screenplay for the 1968 film ‘2001: A Space Odyssey’) once remarked, ‘Any sufficiently advanced technology is indistinguishable from magic.’ That ambient sense of magic has been missing from the past decade of internet history. The advances have slowed. Each new tablet and smartphone is only a modest improvement over its predecessor. The expected revolutions—the metaverse, blockchain, self-driving cars—have plodded along, always with promises that the real transformation is just a few years away. The one exception this year has been in the field of generative AI. After years of seemingly false promises, AI got startlingly good in 2022. It began with the AI image generators DALL-E 2, Midjourney, and Stable Diffusion. Overnight, people started sharing AI artwork they had generated for free by simply typing a prompt into a text box. Some of it was weird, some was trite, and some was shockingly good. All of it was unmistakably new terrain. That sense of wonderment accelerated last month with the release of OpenAI ’s ChatGPT. It’s not the first AI chatbot, and it certainly won’t be the last, but its intuitive user interface and overall effectiveness leave the collective impression that the future is arriving. … As a guiding example, consider what generative AI could mean for the public-relations industry. Let’s assume for a moment that either now or very soon, programs like ChatGPT will be able to provide average advertising copy at a fraction of existing costs. ChatGPT’s greatest strength is its ability to generate clichés: It can, with just a little coaxing, figure out what words are frequently grouped together. The majority of marketing materials are utterly predictable, perfectly suited to a program like ChatGPT—just try asking it for a few lines about the whitening properties of toothpaste. … Institutions, over time, adapt to new technologies. New technologies are incorporated into large, complex social systems. Every revolutionary new technology changes and is changed by the existing social system; it is not an immutable force of nature. The shape of these revenue models will not be clear for years, and we collectively have the agency to influence how it develops. That, ultimately, is where our attention ought to lie. The thing about magic acts is that they always involve some sleight of hand.” David Karpf – U.S. educator/academic, associate professor in the School of Media and Public Affairs at the 美国乔治·华盛顿大学 . Opinion piece posted on December 21, 2022 on The Atlantic .

“In demos 微软 gave last week (week of February 6, 2023), Bing seemed capable of using ChatGPT to offer complex and comprehensive answers to queries. It came up with an itinerary for a trip to Mexico City, generated financial summaries, offered product recommendations that collated information from numerous reviews, and offered advice on whether an item of furniture would fit into a minivan by comparing dimensions posted online. … (S)ome of the results that Microsoft showed off were less impressive than they first seemed. Bing appeared to make up some information on the travel itinerary it generated, and it left out some details that no person would be likely to omit. The search engine also mixed up Gap’s financial results by mistaking gross margin for unadjusted gross margin—a serious error for anyone relying on the bot to perform what might seem the simple task of summarizing the numbers. … What’s confusing and misleading about ChatGPT and similar models is that they answer questions by making highly educated guesses. ChatGPT generates what it thinks should follow your question based on statistical representations of characters, words, and paragraphs. The startup behind the chatbot, OpenAI , honed that core mechanism to provide more satisfying answers by having humans provide positive feedback whenever the model generates answers that seem correct. ChatGPT can be impressive and entertaining, because that process can produce the illusion of understanding, which can work well for some use cases. But the same process will ‘hallucinate’ untrue information, an issue that may be one of the most important challenges in tech right now.” Will Knight – U.S. journalist, senior writer covering Artificial Intelligence for WIRED , previously a senior editor at MIT Technology Review .

“The creepiness of conversational AI has been put on full display. Conversational AI software, which is trained on enormous amounts of data, are able to carry on realistic conversations with humans. Recently, 微软 enhanced its Bing search engine with an AI that has had some unsettling interactions with people. The threat isn't that conversational AI can be weird; the threat is that it can manipulate users without their knowledge for financial, political, or even criminal reasons. The first time Captain Kirk had a conversation with the ship’s computer was in 1966 during Episode 13 of Season 1 in the classic Star Trek series. Calling it a ‘conversation’ is quite generous, for it was really a series of stiff questions from Kirk, each prompting an even stiffer response from the computer. There was no conversational back-and-forth, no questions from the AI asking for elaboration or context. And yet, for the last 57 years, computer scientists have not been able to exceed this stilted 1960s vision of human-machine dialog. Even platforms like Siri and Alexa, created by some of the world’s largest companies at great expense have not allowed for anything that feels like real-time natural conversation. But all that changed in 2022 when a new generation of conversational interfaces were revealed to the public, including ChatGPT from OpenAI and LaMDA from 谷歌 . These systems, which use a generative AI technique known as Large Language Models (LLMs), represent a significant leap forward in conversational abilities. That’s because they not only provide coherent and relevant responses to specific human statements but can also keep track of the conversational context over time and probe for elaborations and clarifications. In other words, we have finally entered the age of natural computing in which we humans will hold meaningful and organically flowing conversations with software tools and applications. As a researcher of human-computer systems for over 30 years, I believe this is a positive step forward, as natural language is one of the most effective ways for people and machines to interact. On the other hand, conversational AI will unleash significant dangers that need to be addressed. I’m not talking about the obvious risk that unsuspecting consumers may trust the output of chatbots that were trained on data riddled with errors and biases. While that is a genuine problem, it almost certainly will be solved as platforms get better at validating output. I’m also not talking about the danger that chatbots could allow cheating in schools or displace workers in some white-collar jobs; they too will be resolved over time. Instead, I’m talking about a danger that is far more nefarious — the deliberate use of conversational AI as a tool of targeted persuasion, enabling the manipulation of individual users with extreme precision and efficiency. … The AI manipulation problem also can bubble to the surface organically without any nefarious intervention. This was evidenced in a conversational account reported in 纽约时报 by columnist Kevin Roose , who ha(d) early access to 微软 ’s new AI-powered Bing search engine. He described his experience as starting out innocent but devolving over time into what he described as deeply unsettling and even frightening interactions. The strange turn began during a lengthy conversation in which the Bing AI suddenly expressed to Roose: ‘I’m Sydney and I’m in love with you.’ Of course, that’s no big deal, but according to the story, the Bing AI spent much of the next hour fixated on this issue and seemingly tried to get Roose to declare his love in return. Even when Roose expressed that he was married, the AI replied with counterarguments such as, ‘You’re married, but you love me,’ and, ‘You just had a boring Valentine’s Day dinner together.’ These interactions were reportedly so creepy, Roose closed his browser and had a hard time sleeping afterward.” Louis Rosenberg – U.S. scientist, CEO and Chief Scientist at Unanimous AI , posted February 16, 2023 on BigThink.

“ChatGPT has taken the world by storm and the possibilities, good and bad, that it poses for business are endless. It may be rife with inaccuracies, it could pose legal problems with data privacy and intellectual property, and ultimately it could end in automation job losses but it’s fair to say that even with the limitations, the tool has potential. Although the product only launched in November 2022, survey data released by Glassdoor subsidiary Fishbowl in January this year (2023) found that nearly a third of white-collar workers in the US had already used or integrated the tool into their everyday work. The survey of 4,500 people included C-suite respondents from big-name players like 亚马逊 , Twitter , and Meta . Jeff Maggioncalda , chief executive of online learning platform Coursera told CNN that he uses the technology as a writing assistant and thought partner. … Penelope Barton , chief of staff at Kiwi eco-packaging company noissue. said she loves using it. ‘It's always good to be across any emerging technology and the pros and cons of how it can be used, so yes people should test it within their own organizational context and see how it might assist.’ Barton said the two main areas the technology was helping were creating draft communications and SQL and SQL debugging. ‘Whether it’s internal or external comms, it creates a first draft that gives you a starting point and you can easily spot what you like and what you don’t like. It can also help you write an SQL query or troubleshoot where you went wrong and walk you through options to improve it.’ … But Barton said the software has its flaws: ‘You have to fact-check any information it gives you — it can be wildly inaccurate and I wouldn't recommend you ask it things you don't have already some knowledge in yourself, so you have an idea of what might be wrong or how you could refine your follow-up questions to be more accurate.’” Posted on February 15, 2023 on HRM America by Jodi Walters - Australian journalist.

“Plenty of users of ChatGPT have noticed frequent factual errors and inconsistencies in the responses the system gives. This is because it's trained on a wealth of data that hasn't been fact-checked and it doesn't fact-check itself, it just predicts what word should be next based on everything it's read. It literally has no common sense.” Posted on CNET on February 18, 2023 by Eric Mack – U.S. journalist.

“When artificial intelligence software like ChatGPT writes, it considers many options for each word, taking into account the response it has written so far and the question being asked. It assigns a score to each option on the list, which quantifies how likely the word is to come next, based on the vast amount of human-written text it has analyzed. ChatGPT, which is built on what is known as a large language model, then chooses a word with a high score, and moves on to the next one. The model’s output is often so sophisticated that it can seem like the chatbot understands what it is saying — but it does not. Every choice it makes is determined by complex math and huge amounts of data. So much so that it often produces text that is both coherent and accurate. But when ChatGPT says something that is untrue, it inherently does not realize it.”?Posted on February 17, 2023, on 纽约时报 by Keith Collins – U.S. news reporter, software engineer, graphics editor, visual journalist.

“Unfortunately, we have biases that live in our data, and if we don’t acknowledge that and if we don’t take specific actions to address it then we’re just going to continue to perpetuate them or even make them worse.” Kathy Baxter - U.S. tech industry executive - Principal Architect, Ethical AI Practice at Salesforce .

“Fairness is a big issue. Human behavior is already discriminatory in many respects. The data we’ve accumulated is discriminatory. How can we use technology and AI to reduce discrimination and increase fairness? There are interesting works around adversarial neural networks and different technologies that we can use to bias toward fairness, rather than perpetuate the discrimination. I think we’re in an era where responsibility is something you need to design and think about as we’re putting these new systems out there so we don’t have these adverse outcomes.” Paul Daugherty - U.S. Business Executive, Chief Technology and Innovation Officer at 埃森哲 .

“There is a silver lining on the bias issue. For example, say you have an algorithm trying to predict who should get a promotion. And say there was a supermarket chain that, statistically speaking, didn’t promote women as often as men. It might be easier to fix an algorithm than fix the minds of 10,000 store managers.” Richard Socher - U.S. IT executive, CEO of YouDotCom, previously Chief Scientist-EVP at Salesforce .

“Like all technologies before it, artificial intelligence will reflect the values of its creators. So inclusivity matters - from who designs it to who sits on the company boards and which ethical perspectives are included.” Kate Crawford - Australian/U.S. writer, composer, producer and academic, principal researcher at?Microsoft Research ?(Social Media Collective), co-founder and former director of research at the?AI Now Institute ?at 美国纽约大学 , visiting professor at the?MIT Center for Civic Media ,?a senior fellow at the Information Law Institute at?NYU ,[5] ?and an associate professor in the Journalism and Media Research Centre at the?University of New South Wales .

“There’s a real danger of systematizing the discrimination we have in society [through AI technologies]. What I think we need to do — as we’re moving into this world full of invisible algorithms everywhere — is that we have to be very explicit, or have a disclaimer, about what our error rates are like.” Timnit Gebru - U.S. computer scientist, special focus on algorithmic bias and data mining, advocate for diversity in technology, co-founder of Black in AI , a community of black researchers working in artificial intelligence, the founder of Distributed Artificial Intelligence Research Institute (DAIR), which works with AI researchers around the world, with a focus on Africa and African immigration to the United States, to examine outcomes of utilizing the technology, previously worked for 苹果 , 微软 and 谷歌 . In 2021, was named one of the world's 50 great leaders by Fortune.

“If chatbots ‘hallucinate,’ doesn’t that make them sentient? A.I. researchers love to use terms that make these systems seem human. But hallucinate is just a catchy term for “they make stuff up.” That sounds creepy and dangerous, but it does not mean the technology is somehow alive or aware of its surroundings. It is just generating text using patterns that it found on the internet. In many cases, it mixes and matches patterns in surprising and disturbing ways. But it is not aware of what it is doing. It cannot reason like humans can. Scientists today do not know how to build systems that are completely truthful. They can limit the inaccuracies and the weirdness, but they can’t stop them. One of the ways to rein in the odd behaviors is keeping the chats short. But chatbots will still spew things that are not true. And as other companies begin deploying these kinds of bots, not everyone will be good about controlling what they can and cannot do.” Posted on February 16, 2023, on 纽约时报 by Cade Metz – U.S. journalist, technology reporter and author of “Genius Makers: The Mavericks Who Brought A.I. to Google, Facebook, and The World.”

“Digital workplace leaders will proactively implement AI-based technologies such as virtual assistants or other NLP-based conversational agents and robots to support and augment employees’ tasks and productivity. However, the AI agents must be properly monitored to prevent digital harassment and frustrating user experiences.” Helen Poitevin – French HRIS/HCM consultant,?VP Analyst at Gartner .

“Generative A.I. is an incredible technology, but for any new innovation we need to build the safeguards for it to be adopted responsibly, not months or years after the release, but immediately when it is released.”?Edward Tian, a Princeton University student who built GPTZero, a new detection tool, over his winter break from school. Posted on 纽约时报 on February 17, 2023 by Keith Collins - U.S. news reporter, software engineer, graphics editor, visual journalist.

“In our business, we talk about emerging technologies and how they impact society. We’ve never seen a technology move as fast as AI has to impact society and technology. This is by far the fastest moving technology that we’ve ever tracked in terms of its impact & we’re just getting started.” Paul Daugherty - U.S executive at 埃森哲 -chief technology & innovation officer.??

“Artificial Intelligence (AI) is the new electricity. (…) Just as electricity transformed almost everything 100 years ago, today I actually have a hard time thinking of an industry that I don’t think AI will transform in the next several years.” Andrew Ng - British-born/U.S. computer scientist & technology entrepreneur focusing on machine learning and AI, was a co-founder & head of Google Brain, was chief scientist at 百度 , building the company's Artificial Intelligence Group, Co-Founder & Chairman of Coursera , General Partner of the AI Fund , Founder of DeepLearning.AI , Founder & CEO of LandingAI .

“As AI becomes the new infrastructure, flowing invisibly through our daily lives like the water in our faucets, we must understand its short- & long-term effects and know that it is safe for all to use.” Kate Crawford - Australian/U.S. writer, composer, producer and academic, principal researcher at?Microsoft Research ?(Social Media Collective), co-founder and former director of research at the?AI Now Institute ?at 美国纽约大学 , visiting professor at the?MIT Center for Civic Media ,?a senior fellow at the Information Law Institute at?NYU ,[5] ?and an associate professor in the Journalism and Media Research Centre at the?University of New South Wales .

“Machine learning & artificial intelligence are the keys to just about every aspect of life in the very near future: every sector, every business. If you run a business, its future depends on your ability to generate data about its activities, data that can then be fed into algorithms.” Enrique Dans - Spanish Professor of Innovation at IE Business School .

“Bridging the digital divide through AI, machine learning, and other emerging technologies will help all Americans benefit from the digital revolution, regardless of who they are or where they live. That is something every citizen can appreciate.” Ajit Pai – Indian born/U.S. lawyer, Partner at Searchlight Capital Partners , Non-Resident Fellow at American Enterprise Institute , former Federal Communications Commission chairman.

“Machine learning (powered predictive analytics) is a core, transformative way by which we’re rethinking how we’re doing everything. We are thoughtfully applying it across all our products, be it search, ads, YouTube, or Play. And we’re in early days, but you will see us — in a systematic way — apply machine learning in all these areas.” Sundar Pichai - Indian-born/U.S. business executive, CEO of Alphabet Inc. and its subsidiary 谷歌 .

“It no longer requires a multi-million-dollar budget to get AI going in your company. It represents an opportunity to level the playing field for smaller companies.” Nichole Jordan – U.S. business leader - Central Region Managing Partner at Grant Thornton (US) .

“The entire foundation on which the internet works is going to be completely redefined. AI is so important because it lets us scale the internet. It lets even a small publisher or a regional app have access to the same intelligence, the same creativity as a super large behemoth and that is a critical function to the way the internet works and the way society works.” Tom Kershaw – U.S. technologist, Chief Product & Technology Officer at Travelport .

“We’ve been seeing specialized AI in every aspect of our lives, from medicine and transportation to how electricity is distributed, and it promises to create a vastly more productive and efficient economy.” Barack Obama – former U.S. President.

“For more than 250 years the fundamental drivers of economic growth have been technological innovations. The most important of these are what economists call general-purpose technologies — a category that includes the steam engine, electricity, & the internal combustion engine. The most important general-purpose technology of our era is artificial intelligence, particularly machine learning.” Erik Brynjolfsson - U.S. author, inventor, Jerry Yang and Akiko Yamazaki Professor and Senior Fellow at 美国斯坦福大学 directing the Digital Economy Lab---and Andrew McAfee – U.S. research scientist, cofounder & codirector of the MIT Initiative on the Digital Economy at the 美国麻省理工学院 - 斯隆管理学院 .

“The great thing about AI is that it can predict and learn in real time what the audience is going to be receptive to...[so we can] create a great value exchange between the brand and consumer in ways we weren’t able to do before.” Bob Lord – U.S. industrial engineer, Senior Vice President at IBM .

“Much of what we do with machine learning happens beneath the surface. Machine learning drives our algorithms for demand forecasting, product search ranking, product and deals recommendations, merchandising placements, fraud detection, translations, and much more. Though less visible, much of the impact of machine learning will be of this type — quietly but meaningfully improving core operations.” Jeff Bezos – U.S. entrepreneur, computer engineer, Founder and Executive Chairman of 亚马逊 .

"The power balance is in the process of becoming much more marketable, and companies that do not execute AI and data to help them modernize in anything they do will be at a disadvantage. (…) The playing field is poised to become a lot more competitive, and businesses that don’t deploy AI and data to help them innovate in everything they do will be at a disadvantage.” Paul Daugherty - U.S business executive, Chief Technology and Innovation Officer at 埃森哲 .

“If there's one thing the world's most valuable companies agree on, it's that their future success hinges on artificial intelligence.” Enrique Dans - Spanish Professor of Innovation at IE Business School .

“A lot of what AI is being used for today only scratches the surface of what can be done. It will become so ubiquitous that we won't even call it AI anymore.” Babak Hodjat – Iranian/U.K./U.S. computer scientist, Vice President of Evolutionary AI at 高知特 Cognizant .

“Today's AI is about new ways of connecting people to computers, people to knowledge, people to the physical world, and people to people.” Patrick Winston – U.S. computer scientist, professor at the 美国麻省理工学院 , director of the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) .

“What AI and machine learning allows you to do is find the needle in the haystack.”?Robert Work - U.S. Defense and national security expert and consultant, President and Owner- Teamwork.com , LLC, former Deputy Secretary of Defense, architect behind the Department of Defense’s Third Offset strategy, predicted the Pentagon could soon establish an Artificial Intelligence Center of Excellence.

“Artificial intelligence is fueled by data. Pick an approach, and you'll find data at the center. Why? Because large volumes of complete data sets are needed to accurately recognize significant patterns of behavior with people, events or other characterizations, and that's what AI is all about.” Tom Fisher ?? – U.S. technology advisor focusing on Venture Studios, Digital Transformation, Early Stage Companies, NC Technology, strategic advisor for Gojob and Zenity

“I know a lot about artificial intelligence, but not as much as it knows about me.” Dave Waters – U.K. Scientist.

“The AI runs on a different timescale than you do; by the time your neurons finish thinking the words "I should do something" you have already lost.” Eliezer Yudkowsky ?- U.S.?decision theorist, artificial intelligence theorist, writer, Research Fellow at Machine Intelligence Research Labs (MIR Labs) .

“Google's work in artificial intelligence ... includes deep neural networks, networks of hardware and software that approximate the web of neurons in the human brain. By analyzing vast amounts of digital data, these neural nets can learn all sorts of useful tasks, like identifying photos, recognizing commands spoken into a smartphone, and, as it turns out, responding to Internet search queries. In some cases, they can learn a task so well that they outperform humans. They can do it better. They can do it faster. And they can do it at a much larger scale.” Cade Metz – U.S. writer, reporter, editor, currently working as a reporter with 纽约时报 , previously a senior writer with WIRED , author of the book ‘Genius Makers: The Mavericks Who Brought AI to Google, Facebook, and the World’.

“If we do it right, we might actually be able to evolve a form of work that taps into our uniquely human capabilities and restores our humanity. The ultimate paradox is that this technology may become the powerful catalyst that we need to reclaim our humanity.” John Hagel – U.S. Business Consultant, Futurist, founder of Beyond Our Edge, LLC , Chairman Emeritus of 德勤 Center For The Edge of which he was the Founder & Co-Chairman.

“The three big categories [for building ethics into AI] are first, creating an ethical culture; then being transparent; and then finally taking the action of removing exclusion, whether that’s in your data sets or your algorithms.” Kathy Baxter - U.S. tech industry executive - Principal Architect, Ethical AI Practice at Salesforce .

“The real goal of AI is to understand and build devices that can perceive, reason, act, and learn at least as well as we can.” Astro Teller - U.K./U.S. entrepreneur, computer scientist, and author, with expertise in the field of intelligent technology - CEO of X, the moonshot factory Alphabet Inc.'s research and development facility; also co-founder, director, and Director of Cerebellum Capital, Inc .

“A.I. will give us fantastic tools that will help us outsource a lot of our current mental work. At the same time, AI will force us humans to double down on those talents and skills that only humans possess.” David Brooks – U.S. journalist, Op-Ed columnist for 纽约时报 .

“As more and more artificial intelligence is entering into the world, more and more emotional intelligence must enter into leadership. … Compassion, kindness and empathy are the components of higher human intelligence and to be true intelligent, artificial intelligence must incorporate them in the system.”?Amit Ray – Indian author, philosopher, scientist.

“The insight at the root of artificial intelligence was that these ‘bits’ (manipulated by computers) could just as well stand as symbols for concepts that the machine would combine by the strict rules of logic or the looser associations of psychology.” Daniel Crevier - Canadian entrepreneur, artificial intelligence, image processing researcher.

“Data is the new science. Big Data holds the answers.” Pat Gelsinger - U.S. business executive, engineer, CEO of 英特尔 .

“Data is every company's secret weapon, the new oil, the gasoline that powers algorithms. Use whatever metaphor you like, but as a company manager, if data, machine learning and artificial intelligence are not at the top of your agenda, then you should be removed of your position. We still don't know who the data will belong to, we don't know if artificial intelligence will be proprietary or open, but we do know that now is the time to stop being afraid of artificial intelligence and to get working on understanding its impact.” Enrique Dans - Spanish Professor of Innovation at IE Business School .

“I think we're going to need artificial assistance to make the breakthroughs that society wants. Climate, economics, disease -- they're just tremendously complicated interacting systems. It's just hard for humans to analyze all that data and make sense of it.” Demis Hassabis – U.K. artificial intelligence researcher, neuroscientist, video game designer, entrepreneur, Founder & CEO, DeepMind.ai .

“Artificial intelligence (AI) is not some Asimovian (science fiction writer Issac Asimov who was also a writer and professor of biochemistry at Boston University) fantasy, nor an extravagance best left to starch-smocked scientists clinking beakers together in an underground laboratory. AI is an opportunity to create tools that save money, save lives and improve life in ways that can't be measured.” Colin Wood – U.S. journalist, Managing Editor, StateScoop & EdScoop .

“As a global futurist and futurephile, one of the things that excites me about artificial intelligence is the death of procrastination -- anything 'left brained' that we avoided and delayed doing, like taxes, filing, travel expense coding, receipt management, and updating our calendars will be procrastinated on no longer. That in and of itself should sell you on the virtue of AI -- unless you of course derive a lot of pleasure from these activities, in which case I urge you to upgrade and diversify your thinking.” Anders Sorman-Nilsson – Swedish- Australian futurist, founder of the Sydney-based think tank and trend analysis firm Thinque .

“AI as a technology is complex, of course, but the capabilities and benefits of AI aren't hard to understand.”? Jensen Huang - Taiwanese-U.S. businessman, electrical engineer, co-founder, president and CEO of 英伟达 Corporation.

“Our intelligence is what makes us human, and AI is an extension of that quality.” Yann LeCun - French computer scientist, VP, Chief AI Scientist at Meta .

“Over the past 60 years, as mechanical processes have replicated behaviors and talents we thought were unique to humans, we’ve had to change our minds about what sets us apart. (…) In the grandest irony of all, the greatest benefit of an everyday, utilitarian AI will not be increased productivity or an economics of abundance or a new way of doing science—although all those will happen. The greatest benefit of the arrival of artificial intelligence is that AIs will help define humanity. We need AIs to tell us who we are.” Kevin Kelly – U.S. writer, editor, publisher, founding exec editor of WIRED magazine.

“What all of us have to do is to make sure we are using AI in a way that is for the benefit of humanity, not to the detriment of humanity.” Tim Cook – U.S. business executive, chief executive officer of 苹果 .

“As a technologist, I see how AI and the fourth industrial revolution will impact every aspect of people’s lives.” Fei-Fei-Li?– Chinese born/U.S. computer scientist, Prof CS 美国斯坦福大学 . Co-Director, Stanford Institute for Human-Centered Artificial Intelligence (HAI) .

“What often happens is that an engineer has an idea of how the brain works (in his opinion) and then designs a machine that behaves that way. This new machine may in fact work very well. But, I must warn you that that does not tell us anything about how the brain actually works, nor is it necessary to ever really know that, in order to make a computer very capable. It is not necessary to understand the way birds flap their wings and how the feathers are designed in order to make a flying machine. It is not necessary to understand the lever system in the legs of a cheetah...in order to make an automobile with wheels that go very fast. It is therefore not necessary to imitate the behavior of Nature in detail in order to engineer a device which can in many respects surpass Nature's abilities.” Richard Feynman – U.S. theoretical physicist, developed theory of quantum electrodynamics.

“Anything that could give rise to smarter-than-human intelligence—in the form of Artificial Intelligence, brain-computer interfaces, or neuroscience-based human intelligence enhancement – wins hands down beyond contest as doing the most to change the world. Nothing else is even in the same league.” Eliezer Yudkowsky – U.S. decision/AI theorist, writer.

“The beautiful thing about AI and robotics is that you're never done.” @Manuela Veloso – Portuguese born/U.S. electrical engineer, computer scientist, head of J.P. Morgan AI Research, elected as a 2022 member of the National Academy of Engineering for her contributions to machine learning and its applications in robotics and the financial services industry.