It seems that the topic of artificial intelligence (AI) is on everyone’s lips these days. And with good reason: according to the Future of Workforce Development report, 62% of hiring managers expect AI to substantially change the nature of work. But this change — depending on who you’re talking to — is charged with mixed emotions from anxiety to excitement.
At Salesforce, we believe AI can improve the way organizations operate (and you can learn how AI is built into our entire Customer Success Platform here).
We've talked to some of the most preeminent AI experts to discuss various intelligence-related topics from emerging technologies, developing unbiased AI, to the future of work. Here are 30 of their most interesting, and sometimes surprising quotes on AI.
AI quotes on business impact
There’s no doubt that AI is already changing how businesses operate — whether through task automation, insight generation, or other use cases. The experts agree that AI is a complex field, and that it’s important to view AI objectively — and to separate science fiction from fact.
“AI is a complex field and I am the first to say that we computer scientists have not progressed as far as many people believe. For instance, we currently have no credible research path to any kind of conscious AI algorithm and there are no robots that are truly autonomous or able to make their own decisions — so don’t worry about walking terminators.” — Richard Socher, Chief Scientist, Salesforce [read the article]
“There’s no one thing that defines AI. It’s more like a tapestry of modern intelligent technologies knit together in a strategic fashion that can then uplift and create a knowledge base that is automated — where you can extrapolate findings from there.” — John Frémont, Founder and Chief Strategy Officer, Hypergiant [watch full panel]
“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, Chief Technology and Innovation Officer, Accenture [read the article]
“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, Director of the MIT Initiative on the Digital Economy [read the article]
“The gradual platformization of AI is very interesting to me. The efforts by Google, Amazon, Salesforce — they’re bringing AI down to a level of not needing to be an expert to use it. … I think the day that any good software engineer can program AI will be the day it really proliferates.” — Kai-Fu Lee, Chairman and Chief Executive Officer, Sinovation Ventures [watch full interview]
AI quotes on workforce readiness
While AI will certainly change how we work, experts don’t foresee huge unemployment or a jobless future; rather they see a shift in skills and questions around talent redeployment. Many hiring managers already know the importance of offering employees opportunities to skill up and retrain.
“I think AI is coming about and replacing routine jobs is pushing us to do what we should be doing anyway: the creation of more humanistic service jobs. ”
Sixty-eight percent of hiring managers say formalized retraining programs are valuable in preparing their workforce for tech advancements according to the Future of Workforce Development report.
“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, Chairman and Director, McKinsey Global Institute (MGI) [watch full panel]
“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.” — Dr. Kai-Fu Lee, Chairman and Chief Executive Officer, Sinovation Ventures [watch full interview]
“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, Chairman and Director, McKinsey Global Institute (MGI) [watch full panel]
“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 Chiu, Partner, McKinsey Global Institute (MGI) [watch full panel]
“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, Director of Data Science, Salesforce [watch full panel]
AI quotes on the future of work
Tech advancements will place rising importance on certain hard and soft skills in the near future. While employees must be able to “speak the language of data” and other hard skills, soft skills are increasingly essential. Judgment calls, creative thinking, and emotional intelligence are in high demand — and not easily replicated by AI. While change can be slow within an organization, experts say that adapting sooner rather than later is key to future success.
“I think what makes AI different from other technologies is that it’s going to bring humans and machines closer together. AI is sometimes incorrectly framed as machines replacing humans. It’s not about machines replacing humans, but machines augmenting humans. Humans and machines have different relative strengths and weaknesses, and it’s about the combination of these two that will allow human intents and business process to scale 10x, 100x, and beyond that in the coming years.” — Robin Bordoli, Chief Executive Officer, Figure Eight [watch full interview]
“My team has a saying: what looks like magic to your competitors in five years is just your good planning. And it really is. It takes a lot of money, work, and effort to get where you’re going with advancements in AI.” — John Frémont, Founder and Chief Strategy Officer, Hypergiant [watch full panel]
“Change is hard within organizations. It’s unclear to me whether or not AI just as a technology is going to radically change all of the challenges that we have within an organization. Things like getting people to change, change their practices and processes, and using this set of technologies. There is a huge gap in terms of what we can do now with AI. There’s improved lead generation that machine learning can do better than humans. And then there’s the Westworld-style ‘is it murder if you kill a robot’ scenario. There’s a big gap between those two things. I think you can start working on understanding the business problems now before you have to worry about Skynet taking over. Knock down the things AI can solve now.” — Michael Chiu, Partner, McKinsey Global Institute (MGI) [watch full panel]
“It’s about having open borders within your organization. The bigger you get, the more siloed you get. It gets very difficult because there’s always political winds blowing this way or that. But when we’re talking about innovation at this scale — and it is here — it’s inevitable. Those who adopt this strategy [of collaborating and strategizing together] will win, and those who do not will lose terribly.” — John Frémont, Founder and Chief Strategy Officer, Hypergiant [watch full panel]
“A lot of times, the failings are not in AI. They're human failings, and we're not willing to address the fact that there isn't a lot of diversity in the teams building the systems in the first place.”
“I think the future of global competition is, unambiguously, about creative talent, and I’m far from the only person who sees this as the main competition point going forward. Everyone will have access to amazing AI. Your vendor on that will not be a huge differentiator. Your creative talent though — that will be who you are. Instead of chasing that race to the bottom on labor costs, invest in turning your talent into a team of explorers who can solve amazing problems using AI as the tool that takes the busy work out. That is the company that wins in the end.” — Vivienne Ming, Executive Chair & Co-Founder, Socos Labs [watch full interview]
"The countries with the highest robot density, have among the lowest unemployment rates. Technology and humans combined in the right way will drive prosperity." — Ulrich Spiesshofer, President and CEO, ABB Ltd. [watch full interview]
AI quotes on biased data
While AI is not inherently good or bad, the data that powers it can be biased, causing skewed and negative outcomes.
Systemic discrimination is a matter that AI experts explicitly warn against. They raise several questions about how we can best increase fairness and not replicate human failings.
“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, Ethical AI Practice Architect, Salesforce [read the article]
“We should be thinking about the values these systems will hold. How will they make decisions if their decision-making is better than ours? Where does that come from? Do we want to give them human values? The same values that also gave us slavery, sexism, racism — some of the more appalling values we hold?” — Liesl Yearsley, Chief Executive Officer, Akin.com [read panel highlights]
“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, Research Scientist, Google AI [watch full panel]
“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, Chief Technology and Innovation Officer, Accenture [read panel highlights]
“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, Chief Scientist, Salesforce [watch full interview]
“Humane technology starts with an honest appraisal of human nature. We need to do the uncomfortable thing of looking more closely at ourselves.” —Tristan Harris, Co-Founder & Executive Director, Center for Humane Technology [read the article]
“A lot of times, the failings are not in AI. They’re human failings, and we’re not willing to address the fact that there isn’t a lot of diversity in the teams building the systems in the first place. And somewhat innocently, they aren’t as thoughtful about balancing training sets to get the thing to work correctly. But then teams let that occur again, and again. And you realize, if you’re not thinking about the human problem, then AI isn’t going to solve it for you.” — Vivienne Ming, Executive Chair & Co-Founder, Socos Labs [watch full interview]
AI quotes on ethics, privacy, and government
AI experts universally agree that there needs to be more discussion and collaboration around AI ethics, privacy, and government regulation.
“The problem that needs to be addressed is that the government, itself, needs to get a better handle on how technology systems interact with the citizenry. Secondarily, there needs to be more cross-talk between industry, civil society, and the academic organizations working to advance these technologies and the government institutions that are going to be representing them.” — Terah Lyons, Founding Executive Director, Partnership on AI [read panel highlights]
“In this era of profound digital transformation, it’s important to remember that business, as well as government, has a role to play in creating shared prosperity — not just prosperity. After all, the same technologies that can be used to concentrate wealth and power can also be used to distribute it more widely and empower more people.” — Erik Brynjolfsson, Director of the MIT Initiative on the Digital Economy [read the article]
“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, Ethical AI Practice Architect, Salesforce [read the article]
“I think one of the most important things that government and industry can do is think beyond bottom line reporting, and more about the AI we deploy itself. This is a more influential technology than we have ever seen. [We need to think about] not just the conversational stuff we’re seeing today, but the future AI that’s going to be making complex decisions on our behalf. What is the impact AI is having on human lives? That’s where we need to go.” — Liesl Yearsley, Chief Executive Officer, Akin.com [read panel highlights]
“By allowing algorithms to control a great deal of what we see and do online, such designers have allowed technology to become a kind of ‘digital Frankenstein,’ steering billions of people’s attitudes, beliefs, and behaviors.” —Tristan Harris, Co-Founder & Executive Director, Center for Humane Technology [read the article]
“Some cultures embrace privacy as the highest priority part of their culture. That’s why the U.S., Germany, and China may be at different levels in the spectrum. But I also believe fundamentally that every user does not want his or her data to be leaked or used to hurt himself or herself. I think GDPR is a very good first step, even though I might disagree with the way it was implemented and the effect it has on companies. I think governments should put a stake in the ground and say this is what we’re doing to protect privacy.” — Kai-Fu Lee, Chairman and Chief Executive Officer, Sinovation Ventures [watch full interview]
“We’re seeing a kind of a Wild West situation with AI and regulation right now. The scale at which businesses are adopting AI technologies isn’t matched by clear guidelines to regulate algorithms and help researchers avoid the pitfalls of bias in datasets. We need to advocate for a better system of checks and balances to test AI for bias and fairness, and to help businesses determine whether certain use cases are even appropriate for this technology at the moment.” — Timnit Gebru, Research Scientist, Google AI [read full interview]
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