China’s zero-Covid policy will hold back a full air travel recovery in the Asia-Pacific region, a top airline industry group warned Tuesday, adding to calls for Beijing to ease its hardline stance.
The world’s second-biggest economy is seeking to stamp out the coronavirus entirely, with rapid lockdowns and mass testing, and the measures have hammered both domestic and international air travel.
The aviation sector’s recovery in Asia was already relatively slow, and Willie Walsh, the International Air Transport Association (IATA) chief, warned Beijing’s approach made the picture bleaker.
“It has been a brutal two years for airlines. But we are seeing signs of recovery now,” he told an aviation conference in Singapore.
“Unfortunately, (the) Asia-Pacific region will lag this recovery as China continues to pursue zero-Covid.”
In 2021 in Asia, international travel was only seven percent of what it was in 2019, compared with a worldwide figure of 25 percent, he said.
While the picture had improved at the start of this year, there was still a “long way to go”, he added.
China’s decision to stick with zero-Covid has put it at odds with many Asian governments, which have started reopening borders and dropping quarantine and testing requirements in recent months.
“The science supports these initiatives,” Walsh told the Changi Aviation Summit, attended by top industry officials.
IATA is “convinced that this science supports the removal of testing and quarantine for unvaccinated travellers from areas of high population immunity, including many parts of this region,” he said.
China, the last major economy still closed off to the world, is facing mounting calls to drop the zero-Covid policy which has left millions in Shanghai locked down for weeks.
Last week, the World Health Organization said the approach was unsustainable.
AI “superusers” seek education, fun, and productivity with generative AI
A look at two separate studies by Sparktoro and Salesforce on people’s generative AI use.
Maybe it was through your job. Or simply out of curiosity.
With the rise of generative AI, you’ve probably tried out ChatGPT or a similar tool. But how often are people using these? More interestingly, what motivates them? Both Salesforce and SparkToro sought to find out with two separate studies.
Here are highlights from each report and how they compare:
Work automation and educational pursuits top priorities for AI users
Both Salesforce and SparkToro can agree on this. SparkToro highlighted professional use of the platform as at an “all-time high,” then ranked categories of interest across over 4,000 ChatGPT prompts with these in the top 5:
- Programming: 29.14%
- Education: 23.30%
- Content: 20.79%
- Sales and Marketing: 13.47%
- Personal & Other: 6.73%
Salesforce found that 75% of generative AI users are motivated by streamlined work communications and task automation. The second highest topic of interest? Technically “messing around” (38%), though a close third was learning and education (34%). Both SparkToro and Salesforce posit that education doesn’t just include homework or university coursework—users also use tools like ChatGPT to develop knowledge of other desired educational topics.
Younger generations more likely to use AI than older ones despite general decline in usage
Salesforce surveyed 4,000 people to find out how they use generative AI and what their demographics are. Turns out, most “superusers” — aka those who use the tool every day — are Millennials or Gen Zers (65%). Plus, 70% of the Gen Z participants surveyed said they use generative AI.
Still, SparkToro notes an overall decline in generative AI use regardless of age. After studying monthly traffic data on OpenAI provided by Datos, SparkToro found overall traffic fell by nearly 30%.
Users ask ChatGPT to write, create, and list
These were the top three common words in SparkToro’s assessment in ChatGPT prompts. However, they also share a notable prevalence of the words “game” and “SEO in prompts as well. Other words less commonly used yet enough to come up in the results included judge, SaaS pricing, curriculum, employment, and employer.
Veronica Ott is a freelance writer and digital marketer with a specialization in finance and business. As a CPA with experience in the industry, she’s able to provide unique insight into various monetary, financial and economic topics. When Veronica isn’t writing, you can find her watching the latest films!
Trends in AI ethics before and after ChatGPT
Computational systems demonstrating logic, reasoning, and understanding of verbal, written, and visual inputs have been around for decades. But development has sped up in recent years with work on so-called generative AI by companies such as OpenAI, Google, and Microsoft.
When OpenAI announced the launch of its generative AI chatbot ChatGPT in 2022, the system quickly gained more than 100 million users, earning it the fastest adoption rate of any piece of computer software in history.
With the rise of AI, many are embracing the technology’s possibilities for facilitating decision-making, speeding up information gathering, reducing human error in repetitive tasks, and enabling 24-7 availability for various tasks. But ethical concerns are also growing. Private companies are behind much of the development of AI, and for competitive reasons, they’re opaque about the algorithms they use in developing these tools. The systems make decisions based on the data they’re fed, but where that data comes from isn’t necessarily shared with the public.
Users don’t always know if they’re using AI-based products, nor if their personal information is being used to train AI tools. Some worry that data could be biased and lead to discrimination, disinformation, and—in the case of AI-based software in automobiles and other machinery, accidents and deaths.
The federal government is on its way to establishing regulatory powers to oversee AI development in the U.S. to help address these concerns. The National AI Advisory Committee recommends companies and government agencies create Chief Responsible AI Officer roles, whose occupants would be encouraged to enforce a so-called AI Bill of Rights. The committee, established through a 2020 law, also recommended embedding AI-focused leadership in every government agency.
In the meantime, an independent organization called AIAAIC has taken up the torch in making AI-related issues more transparent. Magnifi, an AI investing platform, analyzed ethics complaints collected by AIAAIC regarding artificial intelligence dating back to 2012 to see how concerns about AI have grown over the last decade. Complaints originate from media reports and submissions reviewed by the AIAAIC.
SomYuZu // Shutterstock
A significant chunk of the public struggles to understand AI and fears its implications
Many consumers are aware when they’re interacting with AI-powered technology, such as when they ask a chatbot questions or get shopping recommendations based on past purchases. However, they’re less aware of how widespread these technologies have become.
When Pew Research surveyed Americans in December 2022, and asked if they knew about six specific examples of how AI is used, only 3 in 10 adults knew all of them. This includes understanding how AI works with email services and organizing your inbox, how wearable fitness trackers utilize AI, and how security cameras might recognize faces. This low understanding of how AI manifests in daily life contributes to Americans’ attitudes toward this technology. Pew found that 38% of Americans are more concerned than excited about the increase of AI.
As AI works its way into consumer tech, concerns grow to a fever pitch
Concerns about AI initially focused on social media companies and their algorithms—like the 2014 Facebook study when the company’s researchers manipulated 700,000 users’ feeds without their knowledge, or algorithms spreading disinformation and propaganda during the 2020 presidential election.
The viral adoption of ChatGPT and multimedia creation tools in the last year have fueled concerns about AI’s effects on society, particularly in increasing plagiarism, racism, sexism, bias, and proliferation of inaccurate data.
In September 2022, an AIAAIC complaint against Upstart, a consumer lending company that used AI, cited racial discrimination in determining loan recipients. Other complaints focus on a lack of ethics used in training AI tools.
In June 2023, Adobe users and contributors filed an AIAAIC complaint about Adobe’s Firefly AI art generator, saying the company was unethical when it failed to inform them it used their images to train Firefly.
Government, technology, and media emerge as leading industries of concern
While the AIAAIC data set is imperfect and subjective, it’s among the few sources to track ethical concerns with AI tools. Many of the government agencies that have embraced AI—particularly law enforcement—have found themselves on the receiving end of public complaints. Incidents such as facial recognition technology caused wrongful arrests in Louisiana, for example, and a quickly scrapped 2022 San Francisco Police Department policy that would allow remote-controlled robots to kill suspects.
Not surprisingly, many citizens and organizations have concerns about technology companies’ use of AI in the rise of chatbots. Some involving ChatGPT and Google Bard center around plagiarism and inaccurate information, which can reflect poorly on individuals and companies and spread misinformation.
The automotive industry is another sector where major players like Tesla leverage AI in their sprint toward autonomous vehicles. Tesla’s Autopilot software is the subject of much scrutiny, with the National Highway Traffic Safety Administration reporting the software has been connected with 736 crashes and 17 fatalities since 2019.
Chinnapong // Shutterstock
The optimistic case for AI’s future is rooted in the potential for scientific, medical, and educational advancements
As the federal government works toward legislation that establishes clearer regulatory powers to oversee AI development in the U.S. and ensure accountability, many industries ranging from agriculture and manufacturing to banking and marketing are poised to see major transformations.
The health care sector is one field gaining attention for how AI changes may signficantly improve health outcomes and advance human society. The 2022 release of a technology that can predict protein shapes is helping medical researchers better understand diseases, for example. AI can help pharmaceutical companies create new medications faster and more cheaply through more rapid data analysis in the search for potential new drug molecules.
AI has the potential the benefit the lives of millions of patients as it fuels the expansion of telemedicine and has the potential to aid in expanding access to health care; assist with diagnosis, treatment, and management of chronic conditions; and help more people age at home while potentially lowering costs.
Scientists see potential for creating new understandings by leveraging AI’s ability to crunch data and speed up scientific discovery. One example is Earth-2, a project that uses an AI weather prediction tool to forecast extreme weather events better and help people better prepare for them. Even in education, experts believe AI tools could improve learning accessibility to underserved communities and help develop more personalized learning experiences.
In the financial sector, experts say AI warrants a considerable number of ethical concerns. Gary Gensler, the head of the US Securities and Exchange Commission, told the New York Times that herding behavior—or everyone relying on the same information, faulty advice, and conflicts of interest could spell economic disaster if not preempted. “You’re not supposed to put the adviser ahead of the investor, you’re not supposed to put the broker ahead of the investor,” Gensler said in an interview with the New York Times. To address those concerns, the SEC put forward a proposal that would regulate platforms’ use of AI, prohibiting them from putting their business needs before their customers’ best interests.
Story editing by Jeff Inglis. Copy editing by Kristen Wegrzyn.
This story originally appeared on Magnifi and was produced and
distributed in partnership with Stacker Studio.
1 in 5 companies founded in 2021 closed within the year—a story all too familiar in the US
Whether a startup is successful in its first year depends on a variety of factors—from industry type and location to funding and money management strategies. PlanPros investigated what it takes for a business to make it through its first year—a milestone that 1 in 5 companies don’t achieve.
Entrepreneurship is a core tenet of American culture. As many as 55% of Americans have started at least one business in their lifetime, according to a 2019 survey by the Global Entrepreneurship Monitor consortium at Babson College. In fact, there are over 33 million small businesses—which have fewer than 500 employees—in operation today according to estimates from the Small Business Administration. However, the Bureau of Labor Statistics reports that since 1994, about 20% of new businesses have not survived their first year.
The success of a small business affects more than just the business owners’ livelihood. According to the SBA Small Business Facts Report, small businesses are responsible for 2 in 3 jobs created in the past 25 years. Additionally, the SBA estimates that small businesses are responsible for about 44% of all economic activity in the United States.
According to a 2022 Skynova survey of 492 startup founders, 58% said they wished they had done more market research before starting their business. Put simply, market research involves evaluating how likely a product or service is to be received well by its intended customers.
Where a startup is based can have a significant effect on its finances. Business taxes vary across states, as does the availability of various government grant and loan programs designed to aid small businesses. Residents’ purchasing power also ranges geographically. The first-year failure rate for small businesses by state ranged from 18.2% to 36.6% in 2019, the most recent data available—California had the lowest first-year failure rate, while Washington-based startups faced the highest first-year failure rate.
Startups can face certain advantages and disadvantages depending on the nature of their industry as well. According to the Small Business Funding lending agency, small businesses in the health care industry have the highest chance of surviving to at least their fifth year at 60%. Conversely, small businesses in the transportation industry have the lowest chance of surviving through their fifth year at 30%.
Funding and well-managed cash flow
The primary reason new businesses fail is due to a lack of cash or available financial support in its absence, according to the aforementioned Skynova report. In 2022, 47% of startup failures were attributed to a lack of financing or investors, while running out of money contributed to 44% of failures in the same year. A 2019 study funded by the SBA of 1,000 startup small business owners attributes 82% of startup failures to cash flow problems and mismanagement. These data point out the importance of adhering to a strict budget and limiting expenses as much as possible in the first year.
It is also important to identify potential sources of funding or support in advance of any immediate need. This can help prevent running into unsustainable growth. Many government programs exist to help startups survive, including state and federal grants, some of which are designated for certain demographics and industries.
Even after a business is fairly well established, it is important to monitor cash flow closely. Businesses need to survive well beyond just the first year. According to data from the Bureau of Labor Statistics, roughly half of small businesses fail within five years. After 15 years, about 3 in 4 small businesses will have failed.
But the end of a company is not necessarily the end of entrepreneurship for every small business owner. A study by University of Michigan and Stanford economists suggests that business owners who start a second business after their first failures are more likely to succeed on their second attempt.
Story editing by Jeff Inglis. Copy editing by Tim Bruns.
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