Check out the on-demand sessions from the Low-Code/No-Code Summit to learn how to successfully innovate and achieve efficiency by upskilling and scaling citizen developers. Some of the biggest tech names have laid off artificial intelligence (AI) and machine learning (ML) employees this fall, including Meta, Twitter and Amazon. In light of that, it would make sense for industry nerves to be high entering 2023, but that's not the case. Even in the midst of a possible recession, AI experts across several industries told VentureBeat that they expect AI innovation to continue and companies to adjust budgets and priorities accordingly. In fact, these industry leaders resoundingly underscored three areas where AI has thrived over the past year and will continue to grow in 2023: workplace automation and human-centric AI; data-driven AI decision-making; and generative AI use cases.

Non-experts have long made important contributions to machine learning (ML) by contributing training data, and recent work has shown that non-experts can also help with feature engineering by suggesting novel predictive features. However, non-experts have only contributed features to prediction tasks already posed by experienced ML practitioners. Here we study how non-experts can design prediction tasks themselves, what types of tasks non-experts will design, and whether predictive models can be automatically trained on data sourced for their tasks. We use a crowdsourcing platform where non-experts design predictive tasks that are then categorized and ranked by the crowd. Crowdsourced data are collected for top-ranked tasks and predictive models are then trained and evaluated automatically using those data.

In the aftermath of the COVID-19 pandemic, economic activities across some sectors are now reopening with keeping certain preventative measures in place. Organizations are now calling their employees to get back to the work in a limited way. But the impact of the outbreak could lessen the reliance upon human output and lead businesses to adapt to automation in the workplace. As a majority of workforce across the world confined to their homes owing to government-mandated lockdowns, their jobs are being gradually taken over by automation technology. In an effort to keep businesses functioning, companies are increasingly turning to automation in order to manage supply chains and production processes.

Every recession in the past and downturn in modern memory has led to the revolution of tech industry incumbents and the rise of new powers. The brutal recession of the early 1980s gave rise to the personal computer era. In the milder recession of the early 1990s, the federal government essentially handed the internet over to the private sector and laid the seeds for the dotcom boom that gave birth to Amazon, while Microsoft pulled off Windows' victory over Apple. The Great Recession of 2008-2009 hit the technology industry much less harshly than the rest of the economy. While the industry didn't experience any major setback, the downturn did propel the rise of social media in the form of Facebook and Twitter.

You've seen the headlines about robots coming after your jobs, but a new report debunks the fears and finds Americans are less worried about automation in the workplace than it may seem. And it was those "ample fear-based, rhetoric-filled headlines" that prompted the report, Americans' Perceptions of the Future of Work, by the business process outsourcing provider Sykes. The survey of over 1,500 Americans across the US found that over two-thirds (67%) had a positive connotation with intelligent, automation-based technology. SEE: Artificial intelligence: A business leader's guide (free PDF) While that may be the case, demographics play a key role in Americans' perception of robots in the workplace, said Tara Chklovski, founder and CEO of Technovation, a global technology education nonprofit aimed at empowering girls in low-income communities. Technovation conducted its own survey in 2018 of 1,566 low-income families to get a sense of what people are feeling with respect to artificial intelligence and what their fears are.

While scholarship on the topic is getting increasingly nuanced, you're still likely to confront dire warnings about how smart machines are coming to take our jobs. Tesla and Space X CEO Elon Musk says mass automation is "the scariest problem" facing society because "what's going to happen is robots will be able to do everything better than us … I mean all of us." AI pioneer and venture capitalist Kai-Fu Lee believes that the technology could potentially eliminate 40% of existing jobs within the next 15 years. Beyond their inherent pessimism, these kinds predictions have something in common: almost all of them come from men. The vast majority of people funding AI, working on AI, commenting on AI, teaching AI, and starting businesses involving AI are men, what Google researcher Margaret Mitchell calls "a sea of dudes."

The working capacity of employees definitely depends on the training provided to them. AI provides you with a new horizon to discover new forms of technology for better training. For instance, you can use AI powered gadgets that provide practical knowledge to your employees. A simple example of using AI for training is utilizing high-quality audios and videos. You can utilize AI to make the training process more impactful and enjoyable.

Can Japan compete in the global battle for dominance in artificial intelligence and robotics that is under way? A long-standing strength in AI research gives the United States an advantage that is reinforced by the deep bench of AI talent at its numerous universities and tech giants like Apple, Amazon, Facebook, Google and Microsoft. China's government incentives and growing leadership in the mobile economy has led to a data advantage -- its e-commerce giants like Tencent, Alibaba, Baidu and DiDi have an unparalleled view into the minutiae of everyday economic activities across hundreds of millions of consumers, data that feeds into increasingly sophisticated deep learning systems that power AI-native applications ranging from news filtering to medical diagnostics. Japan does not have to be left behind as the U.S. and China race ahead of the rest of the world. But building dominance in this new generation of technologies will require change and planning.

While governments around the world are wrestling with the potential for massive on-rushing technological disruption of work and the jobs market, few are extending the telescope to explore what the knock-on impacts might be for the planet. Here we explore some dimensions of the issue. Although replacing humans with robots has a dystopian flavor, what, if any positives are there from successive waves of artificial intelligence (AI) and other exponentially developing technologies displacing jobs ranging from banker to construction worker? Clearly, the number of people working and the implications for commuting, conduct of their role and their resulting income-related domestic lifestyle all have a direct bearing on their consumption of resources and emissions footprint. However, while everyone wants to know the impact of smart automation, the reality is that we are all clueless as to the outcome over the next twenty years, as this fourth industrial revolution has only just started.

Coding boot camps are becoming almost as popular as college degrees: Code schools graduated more than 22,000 students in 2017 alone. The bet for many is that coding and computer programming will save their jobs from automation, and there's a resulting wave of emphasis on STEM skills. But while a basic understanding of computer science may always be valuable, it is not a future-proof skill. If people want a skill set that can adapt and ride the wave of workplace automation, they should look to -- the humanities. Having knowledge of human culture and history allows us to shape the direction of how technology is developed, identifying what problems it should solve and what real-world concerns should be considered throughout the process.