The AI secret CEOs won't admit: Nobody has figured it out yet
The race to win with artificial intelligence is on, yet many companies might still be reading the user manual.
That's the sense of Sarah Franklin, CEO of the HR software company Lattice.
"People who say that they're super far advanced are just not being honest," she told Business Insider. "There's nobody that's crushing it right now."
That's because generative AI is still a new technology, Franklin said.
"There is nobody today with 10 years of agentic AI experience; we're all on the same starting line," she said.
Sometimes, that line can be blurry.
Lattice drew criticism last year after the company said it would help employers add AI employees to its people platform. The idea was that, like humans, the digital workers would be "onboarded, trained, and assigned goals, performance metrics, appropriate systems access, and even a manager. Just as any person would be," Franklin wrote in a July 2024 blog post on the company's website.
Lattice said days later that it wouldn't pursue adding digital workers in its software product.
However, Franklin said business leaders need to be clear about how they plan to incorporate AI into their operations.
She said one use could be having an AI agent work as a sales development rep, feeding leads to human colleagues.
The technology could talk with customers on a company's website or via phone, sending information about new features, Franklin said. It could also save human sales teams from some of the drudgery of chasing leads.
"Do you really want to pick up the phone all day and do this, or do you want to have some good, qualified prospects to talk to?" Franklin said.
Efficiency at a price
Franklin said that, too often, corporate leaders focus on how AI can bring efficiencies. Instead, she said, the goal should be to help everyone understand the opportunities AI brings to scale themselves.
That means using AI to give workers "superpowers to where they feel like they're stepping into the Iron Man suit" and accomplishing what they need to at work without feeling overwhelmed, Franklin said.
She said that might include using AI to give each employee at a company an executive assistant or an executive coach — the types of resources traditionally limited to the upper ranks because of budget constraints.
Frankin said AI might help everyday workers stay on top of tasks, attend meetings and take notes, and offer tips on how to grow in their roles.
She added that workers might be more willing to ask questions of their Jarvis sidekicks than they would of colleagues because there's no risk of looking silly to AI.
"From a leader's perspective, it's more about focusing on the people first, and then how AI is in service of their success, and then people gravitate toward that," Franklin said.
The missing element
One risk for CEOs who focus on efficiency is that businesses rely too much on bots and not the people who can help a company differentiate itself, said Franklin, who previously worked as chief marketing officer at Salesforce.
That, she said, could lead to robots talking to robots, which would mean there aren't customers to consume a company's service and, ultimately, the business could collapse.
"That's what I think is missing today — is a focus on the people success," Franklin said.
She said she saw recent comments from Anthropic CEO Dario Amodei and OpenAI CEO Sam Altman on the impact of AI as a call to action to learn AI.
Amodei warned in May that AI could wipe out half of entry-level office jobs within five years, while Altman wrote in a recent blog post titled "The Gentle Singularity" that humans had crossed the event horizon by building systems that are "smarter than people in many ways."
These comments, Franklin said, are a reminder that the AI transformation is happening — and that people need to ready themselves. Because we haven't seen past technological revolutions unfold so quickly, she said, the rise of AI can be difficult to digest.
Franklin said that's one reason leaders need to be "transparent, accountable, and responsible" for the path we're taking.
"People are afraid, and we have to be courageous," she said.
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Business Insider
an hour ago
- Business Insider
Does Canada have UBI? Everything you need to know about the country's basic income programs.
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While universal income would be on a universal scale across a population, basic income programs typically target lower-income or vulnerable populations. Organizations in some provinces are testing what basic income could look like on a local level through guaranteed basic income pilots — recurring cash payments geared toward specific groups, like vulnerable populations. While many Canadian politicians across the political spectrum support basic income, some argue that these programs are costly to the local economy. Support from residents, meanwhile, varies. About 60% of Canadians support guaranteed basic income, while 37% support universal basic income, according to a poll published in 2022 by the market research firm Narrative Research. To be sure, cash payments can't replace full-time income or lift everyone out of poverty, but it can give many lower-income residents more opportunities to engage with the economy, said Sheila Regehr, a founding member and chairperson of the Basic Income Canada Network, an organization working to expand basic income access across the country. "From a fiscally conservative perspective, that little bit of investment could save a ton of money down the road and get better results for everything," Regehr told Business Insider, referring to the initial expense and potential benefits of basic income. "This idea we had several generations ago to get a good job, stay in a company for life, that doesn't happen anymore." Shortly after the pandemic began, talks about the efficacy of basic income in Canada accelerated. In 2020, 50 senators sent a letter to Prime Minister Justin Trudeau, Deputy Prime Minister Chrystia Freeland, and Finance Minister Bill Morneau commending them for their actions and calling for a minimum basic income. And in the last federal election in 2021, 189 candidates — representing 46% of Canada's electoral districts — pledged to support basic income. Canada's Parliamentary Budget Officer found that between 2022 and 2023, a universal basic income would cost $87.6 billion but would cut poverty by at least 40% in nearly every province; the cost of poverty totals about $80 billion each year, the PBO estimates. "We certainly have the capacity, there is no question that we do," Regehr said. In 2021, Ontario Sen. Kim Pate introduced Bill S-233 and Winnipeg MP Leah Gazan introduced Bill C-233, creating the country's first national framework for a guaranteed livable basic income for people over the age of 17. Both bills are now under consideration in the Senate. Canada, which has an Old Age Security pension, already has a version of basic income for older residents called the Guaranteed Income Supplement. The GIS is a monthly payment distributed to low-income pensioners aged 65 and older. The maximum monthly payment is $1,087 for someone who is single, divorced, or widowed. "Getting a government check has no stigma to it here; it's just something that happens," Regehr said. Canada's experiments with basic income Basic income experiments in Canada are not new. Talk of implementing a basic income dates back to the 1930s in Alberta, though the first major experiment took place in Manitoba starting in 1974. That project, called Mincome, was studied after completion, and researchers found that participants — who received $3,800, $4,800, or $5,800 a year through 1979 — on the whole continued to work and had higher secondary school graduation rates. Researchers also found that there was an 8.5% drop in hospitalizations for participants at the program's completion. Four decades later, Ontario launched one of the biggest pilots in Canadian history, the Ontario Basic Income Pilot Project. The pilot, whose participants were mostly employed and lower-income, gave up to $16,989 annually for single participants aged 18 to 64 and $24,027 for couples. Ontario Premier Doug Ford's government canceled the pilot just 10 months after payments were first distributed. Reasons for the cancellation included high costs and indications that the program didn't help people contribute enough to the economy. Still, interviews with participants after the pilot found that basic income helped them better afford necessities than traditional welfare payments and assisted in long-term financial planning. A 2020 Canadian Centre for Economic Analysis study determined that a basic income could create 600,000 jobs and contribute $80 billion to Canada's economy in five years, potentially generating $400 billion in additional GDP during that period. Current basic income programs in Canada Various basic income and cash transfer pilots are ongoing, including in Newfoundland and Labrador for people between the ages of 60 and 64. Quebec has a basic income of $1,309 monthly for people with limited income, according to Quebec's government website. Prince Edward Island, which recently hosted a conference on basic income, started its T-BIG pilot — the Targeted Basic Income Guarantee — in 2021 for over 600 people. The program gives cash to participants to bring them within 85% of the federal poverty level. Meanwhile, a few provinces, including Saskatchewan, have debated adopting a sovereign wealth fund that pays dividends similar to the Alaska Permanent Fund. In 2021, the British Columbia Basic Income Panel created 65 recommendations for implementing targeted basic income programs for people with disabilities, young Canadians aging out of government care, and women escaping violence. However, the panel recommended overhauling certain social programs and suggested against a general basic income. "We have concluded that moving to a system around a basic income for all as its main pillar is not the most just policy option," the report reads. "The needs of people in this society are too diverse to be effectively answered simply with a cheque from the government." The province's New Leaf Experiment has seen promising results. In New Leaf's first rendition, launched in 2018, which gave $7,500 total upfront to 50 people experiencing homelessness with a control group of 65 people, participants did not increase spending on goods like drugs or alcohol and spent 99 fewer days unhoused, according to a research note on the pilot's outcomes. The pilot also helped participants with financial literacy and getting them proper IDs and paperwork. Results are forthcoming for another iteration, which started in 2022. "The findings are that they work more hours, they get paid more per hour, and a lot of the individuals we're working with are accessing training," said Amber Dyce, CEO of Foundations For Social Change, a charitable organization that runs the New Leaf pilot. "By getting the cash transfer, they have more breathing room. They're trying to empower themselves to become more financially stable through employment."
Yahoo
an hour ago
- Yahoo
Why is AI halllucinating more frequently, and how can we stop it?
When you buy through links on our articles, Future and its syndication partners may earn a commission. The more advanced artificial intelligence (AI) gets, the more it "hallucinates" and provides incorrect and inaccurate information. Research conducted by OpenAI found that its latest and most powerful reasoning models, o3 and o4-mini, hallucinated 33% and 48% of the time, respectively, when tested by OpenAI's PersonQA benchmark. That's more than double the rate of the older o1 model. While o3 delivers more accurate information than its predecessor, it appears to come at the cost of more inaccurate hallucinations. This raises a concern over the accuracy and reliability of large language models (LLMs) such as AI chatbots, said Eleanor Watson, an Institute of Electrical and Electronics Engineers (IEEE) member and AI ethics engineer at Singularity University. "When a system outputs fabricated information — such as invented facts, citations or events — with the same fluency and coherence it uses for accurate content, it risks misleading users in subtle and consequential ways," Watson told Live Science. Related: Cutting-edge AI models from OpenAI and DeepSeek undergo 'complete collapse' when problems get too difficult, study reveals The issue of hallucination highlights the need to carefully assess and supervise the information AI systems produce when using LLMs and reasoning models, experts say. The crux of a reasoning model is that it can handle complex tasks by essentially breaking them down into individual components and coming up with solutions to tackle them. Rather than seeking to kick out answers based on statistical probability, reasoning models come up with strategies to solve a problem, much like how humans think. In order to develop creative, and potentially novel, solutions to problems, AI needs to hallucinate —otherwise it's limited by rigid data its LLM ingests. "It's important to note that hallucination is a feature, not a bug, of AI," Sohrob Kazerounian, an AI researcher at Vectra AI, told Live Science. "To paraphrase a colleague of mine, 'Everything an LLM outputs is a hallucination. It's just that some of those hallucinations are true.' If an AI only generated verbatim outputs that it had seen during training, all of AI would reduce to a massive search problem." "You would only be able to generate computer code that had been written before, find proteins and molecules whose properties had already been studied and described, and answer homework questions that had already previously been asked before. You would not, however, be able to ask the LLM to write the lyrics for a concept album focused on the AI singularity, blending the lyrical stylings of Snoop Dogg and Bob Dylan." In effect, LLMs and the AI systems they power need to hallucinate in order to create, rather than simply serve up existing information. It is similar, conceptually, to the way that humans dream or imagine scenarios when conjuring new ideas. However, AI hallucinations present a problem when it comes to delivering accurate and correct information, especially if users take the information at face value without any checks or oversight. "This is especially problematic in domains where decisions depend on factual precision, like medicine, law or finance," Watson said. "While more advanced models may reduce the frequency of obvious factual mistakes, the issue persists in more subtle forms. Over time, confabulation erodes the perception of AI systems as trustworthy instruments and can produce material harms when unverified content is acted upon." And this problem looks to be exacerbated as AI advances. "As model capabilities improve, errors often become less overt but more difficult to detect," Watson noted. "Fabricated content is increasingly embedded within plausible narratives and coherent reasoning chains. This introduces a particular risk: users may be unaware that errors are present and may treat outputs as definitive when they are not. The problem shifts from filtering out crude errors to identifying subtle distortions that may only reveal themselves under close scrutiny." Kazerounian backed this viewpoint up. "Despite the general belief that the problem of AI hallucination can and will get better over time, it appears that the most recent generation of advanced reasoning models may have actually begun to hallucinate more than their simpler counterparts — and there are no agreed-upon explanations for why this is," he said. The situation is further complicated because it can be very difficult to ascertain how LLMs come up with their answers; a parallel could be drawn here with how we still don't really know, comprehensively, how a human brain works. In a recent essay, Dario Amodei, the CEO of AI company Anthropic, highlighted a lack of understanding in how AIs come up with answers and information. "When a generative AI system does something, like summarize a financial document, we have no idea, at a specific or precise level, why it makes the choices it does — why it chooses certain words over others, or why it occasionally makes a mistake despite usually being accurate," he wrote. The problems caused by AI hallucinating inaccurate information are already very real, Kazerounian noted. "There is no universal, verifiable, way to get an LLM to correctly answer questions being asked about some corpus of data it has access to," he said. "The examples of non-existent hallucinated references, customer-facing chatbots making up company policy, and so on, are now all too common." Both Kazerounian and Watson told Live Science that, ultimately, AI hallucinations may be difficult to eliminate. But there could be ways to mitigate the issue. Watson suggested that "retrieval-augmented generation," which grounds a model's outputs in curated external knowledge sources, could help ensure that AI-produced information is anchored by verifiable data. "Another approach involves introducing structure into the model's reasoning. By prompting it to check its own outputs, compare different perspectives, or follow logical steps, scaffolded reasoning frameworks reduce the risk of unconstrained speculation and improve consistency," Watson, noting this could be aided by training to shape a model to prioritize accuracy, and reinforcement training from human or AI evaluators to encourage an LLM to deliver more disciplined, grounded responses. RELATED STORIES —AI benchmarking platform is helping top companies rig their model performances, study claims —AI can handle tasks twice as complex every few months. What does this exponential growth mean for how we use it? —What is the Turing test? How the rise of generative AI may have broken the famous imitation game "Finally, systems can be designed to recognise their own uncertainty. Rather than defaulting to confident answers, models can be taught to flag when they're unsure or to defer to human judgement when appropriate," Watson added. "While these strategies don't eliminate the risk of confabulation entirely, they offer a practical path forward to make AI outputs more reliable." Given that AI hallucination may be nearly impossible to eliminate, especially in advanced models, Kazerounian concluded that ultimately the information that LLMs produce will need to be treated with the "same skepticism we reserve for human counterparts."
Yahoo
an hour ago
- Yahoo
Bosses want you to know AI is coming for your job
SAN FRANCISCO - Top executives at some of the largest American companies have a warning for their workers: Artificial intelligence is a threat to your job. CEOs from Amazon to IBM, Salesforce and JPMorgan Chase are telling their employees to prepare for disruption as AI either transforms or eliminates their jobs in the future. Subscribe to The Post Most newsletter for the most important and interesting stories from The Washington Post. AI will 'improve inventory placement, demand forecasting and the efficiency of our robots,' Amazon CEO Andy Jassy said in a Tuesday public memo that predicted his company's corporate workforce will shrink 'in the next few years.' He joins a string of other top executives that have recently sounded the alarm about AI's impact in the workplace. Economists say there aren't yet strong signs that AI is driving widespread layoffs across industries. But there is evidence that workers across the United States are increasingly using AI in their jobs and the technology is starting to transform some roles such as computer programming, marketing and customer service. At the same time, CEOs are under pressure to show they are embracing new technology and getting results - incentivizing attention-grabbing predictions that can create additional uncertainty for workers. 'It's a message to shareholders and board members as much as it is to employees,' Molly Kinder, a Brookings Institution fellow who studies the impact of AI, said of the CEO announcements, noting that when one company makes a bold AI statement, others typically follow. 'You're projecting that you're out in the future, that you're embracing and adopting this so much that the footprint [of your company] will look different.' Some CEOs fear they could be ousted from their job within two years if they don't deliver measurable AI-driven business gains, a Harris Poll survey conducted for software company Dataiku showed. Tech leaders have sounded some of the loudest warnings - in line with their interest in promoting AI's power. At the same time, the industry has been shedding workers the last few years after big hiring sprees during the height of the coronavirus pandemic and interest rate hikes by the Federal Reserve. At Amazon, Jassy told the company's workers that AI would in 'the next few years' reduce some corporate roles like customer service representatives and software developers, but also change work for those in the company's warehouses. IBM, which recently announced job cuts, said it replaced a couple hundred human resource workers with AI 'agents' for repetitive tasks such as onboarding and scheduling interviews. In January, Meta CEO Mark Zuckerberg suggested on Joe Rogan's podcast that the company is building AI that might be able to do what some human workers do by the end of the year. 'We, at Meta as well as the other companies working on this, are going to have an AI that can effectively be sort of a mid-level engineer at your company,' Zuckerberg said. 'Over time we'll get to the point where a lot of the code in our apps … is actually going to be built by AI engineers instead of people engineers.' Dario Amodei, CEO of Anthropic, maker of the chatbot Claude, boldly predicted last month that half of all white-collar entry-level jobs may be eliminated by AI within five years. Leaders in other sectors have also chimed in. Marianne Lake, JPMorgan's CEO of consumer and community banking, told an investor meeting last month that AI could help the bank cut headcount in operations and account services by 10 percent. The CEO of BT Group Allison Kirkby suggested that advances in AI would mean deeper cuts at the British telecom company. Even CEOs who reject the idea of AI replacing humans on a massive scale are warning workers to prepare for disruption. Jensen Huang, CEO of AI chip designer Nvidia said last month, 'You're not going to lose your job to an AI, but you're going to lose your job to someone who uses AI.' Google CEO Sundar Pichai said at Bloomberg's tech conference this month that AI will help engineers be more productive but that his company would still add more human engineers to its team. Meanwhile, Microsoft is planning more layoffs amid heavy investment in AI, Bloomberg reported this week. Other tech leaders at Shopify, Duolingo and Box have told workers they are now required to use AI at their jobs, and some will monitor usage as part of performance reviews. Some companies have indicated that AI could slow hiring. Salesforce CEO Marc Benioff recently called Amodei's prognosis 'alarmist' on an earnings call, but on the same call chief operating and financial officer Robin Washington said that an AI agent has helped to reduce hiring needs and bring $50 million in savings. Despite corporate leaders' warnings, economists don't yet see broad signs that AI is driving humans out of work. 'We have little evidence of layoffs so far,' said Columbia Business School professor Laura Veldkamp, whose research explores how companies' use of AI affects the economy. 'What I'd look for are new entrants with an AI-intensive business model, entering and putting the existing firms out of business.' Some researchers suggest there is evidence AI is playing a role in the drop in openings for some specific jobs, like computer programming, where AI tools that generate code have become standard. Google's Pichai said last year that more than a quarter of new code at the company was initially suggested by AI. Many other workers are increasingly turning to AI tools, for everything from creating marketing campaigns to helping with research - with or without company guidance. The percentage of American employees who use AI daily has doubled in the last year to 8 percent, according to a Gallup poll released this week. Those using it at least a few times a week jumped from 12 percent to 19 percent. Some AI researchers say the poll may not actually reflect the total number of workers using AI as many may use it without disclosing it. 'I would suspect the numbers are actually higher,' said Ethan Mollick, co-director of Wharton School of Business' generative AI Labs, because some workers avoid disclosing AI usage, worried they would be seen as less capable or breaching corporate policy. Only 30 percent of respondents to the Gallup survey said that their company had general guidelines or formal policies for using AI. OpenAI's ChatGPT, one of the most popular chatbots, has more than 500 million weekly users around the globe, the company has said. It is still unclear what benefits companies are reaping from employees' use of AI, said Arvind Karunakaran, a faculty member of Stanford University's Center for Work, Technology, and Organization. 'Usage does not necessarily translate into value,' he said. 'Is it just increasing productivity in terms of people doing the same task quicker or are people now doing more high value tasks as a result?' Lynda Gratton, a professor at London Business School, said predictions of huge productivity gains from AI remain unproven. 'Right now, the technology companies are predicting there will be a 30% productivity gain. We haven't yet experienced that, and it's not clear if that gain would come from cost reduction … or because humans are more productive.' The pace of AI adoption is expected to accelerate even further if more companies use advanced tools such as AI agents and they deliver on their promise of automating work, Mollick said. AI labs are hoping to prove their agents are reliable within the next year or so, which will be a bigger disrupter to jobs, he said. While the debate continues over whether AI will eliminate or create jobs, Mollick said 'the truth is probably somewhere in between.' 'A wave of disruption is going to happen,' he said. Related Content 3-pound puppy left in trash is rescued, now thriving How to meet street cats around the world 'Jaws' made people fear sharks. 50 years later, can it help save them?
