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Tech companies in Canada continue hiring amid reports of slow-down

One startup sector in particular that’s thriving? Quantum computing.

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Toronto tech companies
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Despite reports of layoffs and a general slow-down in Canada’s startup scene, tech companies coast to coast — both Canadian and internationally owned — continue to hire and grow, reports BetaKit

Speaking to BetaKit, HR consultancy owner ​​Nora Jenkins Townson explained that from a company standpoint, the layoff wave has made it easier to hire top talent. 

It makes sense: as workers are let go, hiring managers are able to snap up the best candidates from the pool. At this point, of course, the issue of employee retention comes into play, with companies offering plenty of perks to get the best of the best to stick around.

Jenkins Townson reports that marketing, design, recruiting, and customer service roles are most affected by layoffs, while engineering roles are (unsurprisingly) not.

Of course remote work is both a hiring feature for startups and an increasingly common demand for prospective employees. In a Globe & Mail article on why digital nomads are here to stay, one employer says: “The biggest motivation is just to be able to find talent in general. There are over 200,000 open software developer jobs in Canada and startups are struggling to compete with the Microsofts and Amazons of the world who are able to pay enormous salaries.”

Quantum computing goes wide

One sector that’s seeing quite a bit of growth in Canada is quantum computing — moving increasingly closer to commercialization, as the CBC reports.

Once the domain of academics and governments, these supercomputers are being touted as the key to solving complex problems like climate change. The above CBC articles cites use cases from Goldman Sachs (to improve calculations in options financing) and Volkswagen (manufacturing optimization).

Currently, there are 23 quantum computing businesses in Canada. The fact that there is so much promise for the technology on the horizon means that attracting science-minded talent is a little easier than other sectors. 

Interested in learning which Canadian startups are still actively hiring? BetaKit has put together an extensive list — currently sitting at well over 350 companies — outlining each tech company, their vertical, company size, which offices are hiring (or if they have remote work), and current roles open. Find it here.

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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.

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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.

Read the SparkToro report here and the Salesforce report here

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Trends in AI ethics before and after ChatGPT

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Artificial intelligence is disrupting the world, including by creating ethical dilemmas. Magnifi, an AI investing platform, analyzed complaints collected by AIAAIC to see how AI concerns have grown over the last decade.
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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.


Hands using laptop with AI renderings.

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.

Ethics concerns about artificial intelligence use by companies and governments more than doubled from 2019-2020 according to data collected by independent watchdog group AIAAIC.

Magnifi

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.

A chart showing government as having the most complaints concerning AI, according to data kept by the AIAAIC. Tech and media follow.

Magnifi

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.

Health care professional analyzing tablet and AI concepts.

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.

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1 in 5 companies founded in 2021 closed within the year—a story all too familiar in the US

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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.
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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.

Market research

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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