A June report from the McKinsey Global Institute (MGI) found that, overall, artificial intelligence adoption is still slow; only 20 per cent of “AI-aware” businesses say they are adopters.
The MGI report on AI discussed the difference in AI investment and adoption, with investment in AI technologies experiencing a threefold external investment growth since 2013. Compared to that figure, 41 per cent of firms told MGI that they are uncertain about the benefits, and within that 20 per cent of adopters, 10 per cent are adopters of three or more AI-backed technologies.
A new report from Harvard Business Review on the two major business potentials of AI said that while this may be the trend on average, “senior executives know that AI isn’t just hype.”
HBR attributes some of the hesitancy to adoption to business leaders not being sure where they should be applying AI, and after McKinsey researchers Michael Chui, Nicolaus Henke and Mehdi Miremadi took a closer look at 400 AI use cases from 19 different industries, and nine business functions, they found that the question of where to put AI to work in a business is a matter of playing “follow the money.”
“The business areas that traditionally provide the most value to companies tend to be the areas where AI can have the biggest impact,” the report explains.
The two areas that HBR found to the implementation of AI to have the biggest impact are: supply-chain management/manufacturing and marketing and sales.
Chui, Henke and Miremad also found that another way for businesses to find an area to introduce AI is “to simply look at the functions that are already taking advantage of traditional analytics techniques.” Meaning that business leaders should look to apply AI to parts of the company where neural network techniques could provide a higher performance, or “generate additional insights and applications.”
According to the MGI report, companies that have a low AI adoption rate are in the education, health care, and travel/ tourism sectors.
In a previous Digital Journal article on how hospitality brands can undergo digital transformation, it was stressed that “hospitality brands can use new technologies to make their businesses hyper guest-focused.” Utilizing AI for marketing and sales purposes is just one way of making that happen.
Robots are starting to deliver takeout orders. Are they here to stay?
In a March 2023 Deloitte survey, 47% of Americans said they would order from a restaurant that delivers food with a drone or an autonomous vehicle. That’s up 3 percentage points from the company’s 2021 survey about restaurant trends.
In that first survey, researchers noted there was “massive uncertainty in the industry, and many worried that restaurant patronage might never recover” from the COVID-19 pandemic. It found that two-thirds of consumers believed they would not immediately return to their pre-pandemic restaurant habits.
In 2023, most restaurant customer behavior is back to normal—though some changes have blended into the industry’s practices. Task Group analyzed the state of autonomous delivery systems, both nationally and internationally, to measure the progress of this technology post-pandemic.
As with other industries, technology has helped maximize efficiency and improve customer satisfaction. Business owners learned new service methods, marketing strategies, and technical terminology. Food delivery skyrocketed during lockdowns, making greater strides in restaurant efficiency and, in some cases, profits. Many restaurant owners connected apps that allowed customers to order without talking to a human to state-of-the-art delivery systems that don’t require a driver.
Restaurants and transportation companies in North America and Europe are experimenting with new automated delivery techniques that can reduce their costs as long as they do not compromise customer satisfaction. And consumers are ready—but how soon will it become standard practice?
Julija Sh // Shutterstock
What are drones and sidewalk delivery vehicles?
The robots most commonly used in the food delivery industry are aerial drones and wheeled autonomous delivery vehicles that travel along sidewalks to reach customers.
Drones are classified by how they generate lift—with fixed wings, rotors, or a combination—by how they’re used, such as food delivery, and what equipment they have on board, including batteries and cameras.
In the U.S., the Federal Aviation Administration regulates drone use. The agency requires pilots to be certified—and bans drones within five miles of airports.
For many years, the FAA stood in the way of companies seeking to use drones for deliveries, but in 2019, the agency agreed to allow uncrewed delivery flights beyond the pilot’s line-of-sight by UPS and Wing Aviation, owned and operated by Google’s mothership Alphabet. Since then, the agency has approved drone delivery operations for several companies, including Amazon and Walmart.
According to a study published by the Harvard Kennedy School in 2022, autonomous delivery vehicles are not the future. They’re already here. Self-driving machines about the size of a large cooler are already traveling down our sidewalks and crosswalks to deliver various packages.
Policymakers question how these vehicles will work and interact with people and other vehicles in already congested and chaotic urban environments. The Harvard researchers believe these vehicles “offer the promise of less congestion and greener shipments,” but also “raise concerns about safety and use of road and sidewalk infrastructure.”
While the debate continues, the manufacturers of these robots continue to advance their technology, including using machine learning to improve navigation, efficiency, and safety.
How far off are drone or sidewalk deliveries?
Estonia-based delivery startup Bolt, working with Starship Technologies, has been trialing sidewalk deliveries in Estonia, the U.K., and the U.S. and plans to formally launch robot deliveries later this year in as many as 500 cities in 45 countries.
Bolt’s main competitor, Uber, signed a deal in 2022 with autonomous vehicle startup Nuro “to test driverless food deliveries” in Mountain View, California, and Houston, Texas. Before the agreement, Uber ran a pilot program for sidewalk delivery in Los Angeles, while Nuro delivered Domino’s pizzas in specific areas of Houston for a year.
Story editing by Jeff Inglis. Copy editing by Kristen Wegrzyn.
This story originally appeared on Task Group and was produced and
distributed in partnership with Stacker Studio.
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.
Events2 months ago
Where will AI go next?￼
Business4 months ago
How to build company culture in a scale-up
Events6 months ago
The innovator’s mindset and the battle between Batman-v-Superman: mesh conference day 2
Business4 months ago
How to build and maintain a company culture among a remote workforce
Events6 months ago
3 big ideas animating day one of the mesh conference