Synthetic Savants
Since the introduction of consumer-facing artificial intelligence applications such as ChatGPT and Google’s Bard, generative AI has transformed how people work around the world. How might it impact specific industries in the years to come?
As generative AI sweeps the world, how will it transform the way we work and innovate?
We live in an age of intelligent machines. Since the introduction of consumer-facing artificial intelligence (AI) applications such as OpenAI’s ChatGPT and Google’s Bard over the past year, generative AI has transformed how people work around the world.
From $40 billion in 2022, the market size for generative AI will balloon to $1.3 trillion over the next 10 years, according to Bloomberg Intelligence. First popularized through image generators, the technology has been applied in fields ranging from neuroscience to advertising, sometimes in surprising ways.
Generative AI programs like the large language models powering ChatGPT are trained on enormous volumes of data to sense patterns and predict how they will play out in a piece of content. These models can be trained on linguistic, financial, scientific, sensor, or other data—especially data that is uniform and structured—and can then create new content in response to user input. They have had remarkable success, particularly in image and text generation, and have seen rapid uptake in sectors ranging from education to computer programming. “This technology is set to fundamentally transform everything from science, to business, to healthcare … to society itself,” Accenture analysts enthused in a report. “The positive impact on human creativity and productivity will be massive.”
Powerful New Assistants
Generative AI first gained public attention thanks to its ability to change how we communicate through words, images, and video. It’s no wonder, then, that the world’s largest public relations company has embraced it. Edelman worked with OpenAI to launch the original ChatGPT-2 and delivered the first application in an ad campaign. In the spots for Hellmann’s Mayonnaise, the tool is tasked with finding new ways to use leftovers.
Edelman believes the technology will reconfigure the communications industry, but it won’t replace human ingenuity, strategic advice, and ethical decision-making that builds trust, said Meghan Barstow, president and representative director of Edelman Japan.
“We predict that AI will become an essential assistant in our work, helping to brainstorm, research, summarize, trend spot, monitor media, and generate content, among other tasks,” explained the ACCJ governor and chair of the chamber’s Communications Advisory Council. “The emphasis here is on ‘assistant,’ as we believe there will always be a human in the loop, that AI and people working together will provide the most effective and valuable work output.
“As with any technology, there are risks that require appropriate caution, education, processes, and policies to ensure the safe and trustworthy use of generative AI to protect our work, our clients, and end users from issues related to disinformation, bias, copyright infringement, and privacy.”
Similarly, lawyers such as Catherine O’Connell are also using generative AI as smart assistants. O’Connell is principal and founder of Catherine O’Connell Law and co-chair of the American Chamber of Commerce in Japan (ACCJ) Legal Services and IP Committee.
After taking a course on how to get the most out of ChatGPT, she has been using it for writing keynote speeches, article outlines, posts on social media, and skeletons of presentations. She compares the tool to a human intern, and praises its time-saving efficiencies, but warns that it should not be used for legal work, such as contracts or legal advice. Attorneys in the United States, she noted, have found themselves in trouble after producing legal filings referencing non-existent cases that generative AI simply made up.
“Generative AI is like a teenager that has a lot of promise but has not learned how to be a whole professional yet; it needs guidance,” said O’Connell. “However, in terms of an idea generator or idea expander, a time-saving device, and an assistive tool, generative AI is an asset. The rest falls to me to add my human touch to check and verify, to add my own personality and insights only I have, and to make the output my very own. I think generative AI is so good that its cousin, Google search, may be out of a job sometime soon.”
Smart Tools for Talent
Recruiting is another industry in which workers deal with mountains of structured data, in the form of resumes and online posts, that can be utilized by AI. Robert Half Japan, an ACCJ Corporate Sustaining Member company, uses a system called AI Recommended Talent (ART) to match resumes to client needs. The system speeds up matching for job hunters and employers, allowing staff to spend more time with clients.
“The real power of generative AI is how much it can integrate with our existing systems,” explained Steven Li, senior division director for cybersecurity. “We are piloting ChatGPT-4 integration in our Salesforce CRM. Studies have shown benefits from integrating generative AI into workflows. Other industry examples that highlight the benefit of integration include the GitHub CoPilot generative AI feature.”
The effectiveness of AI in recruiting has led some people to speculate that it could render many human recruiters obsolete. Deep learning algorithms are figuring out what a good resume looks like, and generative AI can craft approach messages and InMails, a form of direct message on the popular LinkedIn platform, noted Daniel Bamford, Robert Half’s associate director for technology.
“However, the real value of agency recruitment is not, and never was, a simple job-description-to-resume matching service,” added Bamford. “Agency recruitment done well is a wonderful journey of problem-solving, involving the goals of organizations and teams and the values and desires of individuals. Excellent recruiters will thrive. They will use AI’s capacity to handle simple tasks like scheduling and shortlisting. This will free up time for high-value interactions, delivering even greater value for their partners and industries through the human touch. The future of excellent recruiters will be brighter with AI’s support.”
Tracking Ships and Patients
Even a traditionally hardware-oriented industry like logistics is being transformed by generative AI. Shipping giant Maersk is using a predictive cargo arrival model to help customers reduce costs with more reliable supply chains. It also wants to harness the power of AI to recommend solutions when shipping routes are congested, advising on whether goods should be flown or stored, and better understand the sales process, Navneet Kapoor, Maersk’s chief technology and information officer, told CNBC.
Maurice Lyn, head of Managed by Maersk for Northeast Asia, also sees great potential in the technology. “The biggest changes that I foresee will be related to the enhanced visibility into, and agility of the management of, the global supply chains of our clients on an execution level,” he told The ACCJ Journal. “The data aggregated will allow logistics service providers [LSPs] to deliver predictive and proactive solutions to our clients. If clearly interpreted by the LSPs, stability and uniformity of costs and deliverables will be provided globally and locally to our clients.”
Generative AI may even help us live longer, healthier lives via long-term patient monitoring. Sydney-based medical AI startup Prospection recently launched its first generative-AI model in Japan to analyze anonymized patient data for pharmaceutical companies so they can better understand patient needs. A Japanese drug company, for instance, could look at cancer patient outcomes across the country and find that they are slightly worse in a particular region, possibly because less-effective drugs are prescribed there.
Founded in 2012 and operating in Australia, Japan, and the United States, Prospection now has data on half a billion patients. For the first 10 years, it was using traditional AI methods, but generative AI has opened new services for the company. Users can query Prospection’s AI services about typical pathways for patients who took a certain drug, or what therapy they underwent after quitting the medication. A Prospection model can predict whether a patient will experience a certain event, such as needing to be hospitalized, over the next year.
“The ChatGPT transformer model is trained on billions of sentences consisting of words. We see each patient’s journey as the sentence and events in the journey as the words. That’s the vocabulary,” said Eric Chung, co-founder and co-CEO of Prospection. “The data is very powerful. There are lots of insights to be gained from data on 500 million patients. It’s beyond the power of humans to analyze, but AI can do it.”
Investing in Smart Agriculture
AI gets a lot of attention these days, but its application to farming is not often in the spotlight. Sagri Co., Ltd. uses AI, machine learning, and mapping technologies to solve social problems. I had the opportunity to talk with CEO Shunsuke Tsuboi about the challenges that agricultural technology startups in Japan face when it comes to funding, as well as the benefits of their technology.
Japan startup Sagri is transforming family farming with AI
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Artificial intelligence (AI) gets a lot of attention these days, but its application to farming is not often in the spotlight.
Recently, I had the opportunity to talk with Shunsuke Tsuboi, chief executive officer of Sagri Co., Ltd., which uses AI, machine learning, and mapping technologies to solve social problems.
On my podcast, Disrupting Japan, Tsuboi and I discussed the challenges that agricultural technology (agtech) startups in Japan face when it comes to funding, as well as the benefits of their technology.
Taking Root
Sagri was founded in June 2018 and uses satellite imaging and data to analyze farmland. The technology scans areas of up to 10 hectares in size, making it particularly suited to Japan, where farms are generally small. The data can be accessed using a smartphone app, and the goal is to help farmers better understand the condition of their soil and identify the best time for harvesting.
The idea for the company took shape in a laboratory at Yokohama National University, where Tsuboi is a mechanical engineering graduate student. His lab is using space-based technology to examine soil, and he and his business partners have been able to apply some of this to their platform, which shares the name of the company.
Applications
If you’ve walked around the Japanese countryside, you’ve probably seen small plots of abandoned farmland. Sometimes these even intermingle with residences in neighborhoods not far outside the capital.
Whether farmland is in use or abandoned makes a difference from a tax perspective, so the government manually checks the status of land each year. The AI behind Sagri’s analysis can determine with 90-percent accuracy whether a field is abandoned, drastically reducing the amount of work required of government staff.
Apart from taxation, the government is also interested in identifying farmland that can be revitalized. Satellite data that provides soil analysis can make that process easier.
Tsuboi noted that a big reason for the abandonment is that the farmers are getting older and are unable to maintain the land. One benefit of the Sagri platform is that machines can receive the data analysis and automatically perform tasks such as applying fertilizer.
Beyond Japan
Agtech is an area in which Japan has a great opportunity to be a world leader, and Sagri is putting its technology to work in India, where there are also many small farms. But getting the financing needed to keep operations going can be difficult. Sagri believes it has a solution.
“Many Indian farmers need loans, but they don’t have the chance to get them,” Tsuboi said. Because there are so many farmers, it is difficult for banks to spread enough money around. To have a better chance of funding, farmers want to show banks that they are a good investment, he explained. Banks cannot get that sort of information using present methods, but the satellite data analysis provided by Sagri can allow them to check the farmland’s condition and potential yields.
Tsuboi sees Africa as the company’s next market, noting potential in countries such as Kenya and Rwanda. Areas of Southeast Asia are also within Sagri’s sights.
Funding
There are not many agtech startups in Japan, but it seems that there should be. With lots of small farms, lots of creative people working on agtech at universities, and venture capitalists (VCs) with money to invest, why don’t we see more?
Tsuboi feels one reason is that VCs and the government both see farmland as low-growth opportunities. And attracting money from abroad, such as from Silicon Valley VCs, is not easy because they are focused on large-scale industrial farming. The farms on which Sagri is focused in Japan and India are too small to attract their interest.
But Sagri has had some success inside Japan, and announced in June that they have secured ¥155 million ($1.4 million) in funding from a group led by Real Tech Holdings Co., Ltd., who was joined by Minato Capital Co., Ltd., Senshu Ikeda Capital Co., Ltd., and Hiroshima Venture Capital Co., Ltd. Also participating is Bonds Investment Group Co., Ltd., whose Hyogo Kobe Startup Fund, established in March, is making its first investment.
Sagri is a great example of a Japanese startup that can assist people at home and also have a much bigger impact—and earn a much bigger profit—abroad. Globally, the company can help millions of small family farms thrive, and they can bring great returns for investors in the process.