Automation will create new types of jobs.
Delivery robots seem to be everywhere these days. Keeping them out of trouble are human minders who might need to hop on a bike to finish the delivery themselves.
Continue reading “Who’s driving that food delivery bot? It might be a Gen Z gamer” »
Rather than fret about how many jobs future technologies will destroy, we should focus on how to shape them so that they complement the workforce of tomorrow.
Traditional wisdom says that 3D printers are unsuitable for manufacturing. There are several reasons for that, including cost, part quality, and time, but labor is one of the most significant challenges. With conventional 3D printers, an operator must remove parts between jobs. That has a cost and slows down large production runs. Belt 3D printers solve this problem and also allow for infinite printing in one axis. Tinybelt, a new 3D printer on Kickstarter right now, makes this technology affordable.
The Tinybelt Kickstarter campaign is currently a third of the way to its $80,000 funding goal and needs your help to reach that goal. But you won’t want to contribute out of a sense of charity — you’ll want to back this campaign because Tinybelt has a lot to offer at an extremely competitive price. Tinybelt’s closest competition, the Creality CR-30 “3DPrintMill,” costs about $1,050. Tinybelt is available on Kickstarter right now for $499. Even at that low price, Tinybelt has a larger build volume than the competition.
As with other belt 3D printers 0, Tinybelt has one axis that is infinite. That means you can print parts as long as you want or print an unlimited number of parts—or both. The other two axes are 300mm and 200mm, which is almost twice the area of the Creality CR-30. A special nozzle made by Slice Engineering for the Mosquito hot end allows for printing at a shallower angle. Other specs are comparable, including the use of a dual-gear Bowden extruder.
Tesla’s Fremont Factory could have its production capacity increased, according to CEO Elon Musk. Tesla is “considering expanding [Fremont] significantly,” Musk said in a Tweet last night.
Following Musk’s heavily publicized jab at President Joe Biden on Tuesday night for not mentioning Tesla in the State of the Union Speech with the likes of Ford and GM, who received Biden’s praise for electric vehicle projects resulting in employment opportunities. While Biden commended Ford for $11 billion invested and 11,000 new jobs and GM for $7 billion and 4,000 new employment opportunities in Michigan, Musk hit back with a valid point.
“Tesla has created over 50,000 US jobs building electric vehicles & is investing more than double GM + Ford combined,” he said, alerting “the person running this account” to give Tesla more credit.
Topic: James Hughes — The Future of Work (Future Day Talk) Time: Mar 1, 2022 08:00 AM Canberra, Melbourne, Sydney Join Zoom Meeting https://us02web.zoom.us/j/81306102463?pwd=eDBldno3cUdZZGcxVHoxNEJ1RkgrUT09 Meeting ID: 813 0610 2,463 Passcode: Q6VzpF
As part of the annual Future Day celebration, James Hughes will join us that may concern you — ‘The Future of Work’. Zoom details coming soon!
Abstract: The pandemic has launched a debate about the future of work around the world. Those who can work remotely have often found they prefer remote or flexible, hybrid options. The Great Resignation has put upward pressure on wages and benefits in the service sector, encouraging the implementation of automation. Climate change mitigation is encouraging a shift towards “green jobs.” Rapid changes in the labor market have made the payoffs of higher education uncertain for young people, while many societies are entering an old-age dependency crisis with too few workers paying taxes for growing numbers of pensioners. Before the pandemic proposals for universal basic income (UBI) were seen as necessary adaptations to imminent technological unemployment, and the during the pandemic many countries provided temporary UBI to keep people safe. We are now poised for a global discussion about whether we need to work at all, and what kinds of jobs are desirable.
Before the pandemic started (ah, those glorious days…) a collective panic was mounting over automation and robots gradually replacing workers in various fields, or “stealing our jobs,” as the common refrain went. These worries haven’t subsided two years later, but they’re being countered by severe and largely unexpected labor shortages across multiple sectors of the economy. One of the industries that’s struggling most is restaurants. While we may still encounter automation-related unemployment problems down the road, right now it seems robots are lending a much-needed hand in food service.
One of these robots is none other than Flippy, initially debuted in 2017 to flip burgers at a California fast food chain. Since then Miso Robotics, Flippy’s maker, has expanded the bot’s capabilities, creating a version that can cook chicken wings, fries, and other greasy delights. This week also brought a significant expansion to Flippy’s presence as White Castle announced plans to install the robot at more than 100 restaurants this year.
Continue reading “Flippy the Fast Food Robot Just Got Hired in 100 Restaurants” »
Work remotely, work more jobs.
With the pandemic’s turbocharged acceleration of remote work options, many employees have sought to capitalize on the lack of personal supervision by secretly working two (or more) full-time jobs at once. But while there’s more money to be made, the strategy brings with it significant tradeoffs, namely mental health.
Continue reading “How Remote Workers Are Secretly Juggling Two Full-Time Jobs” »
In part because the technologies have not yet been widely adopted, previous analyses have had to rely either on case studies or subjective assessments by experts to determine which occupations might be susceptible to a takeover by AI algorithms. What’s more, most research has concentrated on an undifferentiated array of “automation” technologies including robotics, software, and AI all at once. The result has been a lot of discussion—but not a lot of clarity—about AI, with prognostications that range from the utopian to the apocalyptic.
Given that, the analysis presented here demonstrates a new way to identify the kinds of tasks and occupations likely to be affected by AI’s machine learning capabilities, rather than automation’s robotics and software impacts on the economy. By employing a novel technique developed by Stanford University Ph.D. candidate Michael Webb, the new report establishes job exposure levels by analyzing the overlap between AI-related patents and job descriptions. In this way, the following paper homes in on the impacts of AI specifically and does it by studying empirical statistical associations as opposed to expert forecasting.
Second, we need to be aware of the manifest biases and fallacies that magnify the weight humans put on potential losses compared to potential future gains. As a result of these biases, humans often seek to preserve the status quo over pursuing activities that lead to future changes, even when the expected (but risky) gains from the latter may outweigh those of maintaining the status quo. The preference for the status quo, and neat narratives that oversimplify complex scenarios, can lead to overlooking (or ignoring) important information that is not consistent with the current generally accepted meme — illustrated, perhaps, in Musk’s continued optimism for autonomous vehicles despite the evidence leading to others downscaling their forecasts.
The first and second points together lead to the third important consideration: the importance of independently verified data over forecasts and opinion in determining the need for and appropriateness of policy interventions. And data is historical by nature. Pausing to collect it rather than rushing to respond is recommended.
To that end, we can use available data to analyze whether increasing use of AI is demonstrably affecting key labor market performance indicators: labor productivity and multifactor productivity growth. If, as Keynes suggests, AI-driven technological change is increasing the potential for new means of economizing the use of labor to outrun the pace of finding new ways to use it, we would expect to see both statistics rising in the era dominated by AI. Yet as Figures 1 and 2 show, the exact opposite appears true for a wide range of OECD countries. Neither does the data suggest that other key labor market indicators have changed negatively with the advent of AI. As with the computer industry, we see the effects of AI everywhere but in the productivity statistics.
