Smarter Worklife
AI has existed in our imaginations for a long time. The dream of an automated world that redefines the boundaries of what is possible has driven our visions of the future and triggered endless curiosity. But how close are we to a paradigm shift in the working world?
It’s on everyone’s lips, from schoolyards to boardrooms to senior centers. One AI tool after another has been launched in rapid succession, and it only took two months for OpenAI’s chatbot ChatGPT to reach 100 million users. That’s the fastest growing user group in internet history so far. By comparison, it took nine months for the TikTok app to reach the same number of users.
Enthusiasm for AI has gone in waves since the 1950s. Expectations have varied, but the goal of emulating human abilities through algorithms was difficult for the weaker computers of yesteryear to achieve.
Sverker Janson is the director of the Center for Applied AI at the Research Institutes of Sweden, RISE. He coordinates and leads the development of AI in a variety of fields in Sweden—from agriculture to telecoms and energy—with the mission of helping businesses and public sector agencies understand the technology and how it can be used. He has been monitoring the accelerating capabilities of AI.
“Slowly but surely, a bit after the turn of the millennium, machine learning began to evolve,” Jansson says. “Around 2012, the world was astonished that an AI was able to describe the contents of a photograph. Today, not many years later, that seems pretty tame.”
When apps like ChatGPT and the image generator Midjourney were released in 2022—both examples of generative AI with the ability to create new content based on the information they are trained in—the accessibility of AI tools mushroomed, placing these tools in the hands of everyday people. It was the launch of these tools that lit the fuse of the AI explosion we see today. In early 2022, the Meta company released its version of an AI model as open source, which meant that it can be used freely to implement in apps or other software.
“There’s no question that ChatGPT has released a massive force and creativity,” Janson says. “We’re likely to see an explosion of new services based on functions similar to those of ChatGPT. Open source has made it possible lately for anyone in the world to include them in apps.”
Major players in the tech industry have long been following developments in the AI field. We can clearly see the race between giants like Google and Microsoft in the vast amounts of money they are sinking into various projects. In early 2023, Microsoft invested a whopping USD 10 billion in OpenAI.
“It’s a big deal, and Microsoft is only one of many companies that realize how hugely disruptive this is,” Janson says.
Although AI has long been used in various fields, such as healthcare and finance, it has only now made the transition from mysterious to matter-of-fact for more people. But exactly how we’re going to interact with AI in the workplace remains to be seen.
“This particular type of chatbot, like ChatGPT, will soon become a very normal element for us in our jobs,” Janson predicts. “All AI that has been used professionally has been very limited so far, for example in data analysis, looking for anomalies in data streams. At the core, these are the same technologies, but now that they have been trained with more and richer data, they are capable of much more.”
The answer to where generative AI will be used in work isn’t far away, Janson says.
“The only limit to progress right now is access to a reliable analog to ChatGPT that can be used in more sensitive contexts with an organization’s confidential data. But that is sure to come in the near future.”
It’s hard to say how AI will affect us in the future, but many parts of society are likely to face major challenges. Just as with all new technology, moral and ethical guidelines will need to be established, as well as legislation. Some experts say it would be best to press pause on AI considering how fast things are developing.
“OpenAI and other players have had to put a huge amount of work into putting limits on ChatGPT so it doesn’t, for example, tell people how to build a bomb. Disinformation has been a major problem for a long time, and with AI models it could be produced on a gigantic scale. There would be an enormous risk of encountering a smart automated internet troll.”
There is no doubt that AI is something we need to learn to use in our daily lives. Janson compares its development with the introduction of computers in workplaces.
“Perhaps this sounds a bit dark, but technology keeps advancing. People who refused to use computers when they started appearing in the workplace were replaced with others who were prepared to learn to use them. Companies that don’t make use of the possibilities of AI will be replaced.”
The dream of AI is starting to become reality, with massive investments from companies, and despite ethical concerns that crop up along the way, the world faces an exciting future. Janson doesn’t believe that humans will become obsolete on the job market any time soon. Human creativity and judgment are important dimensions to refine anything produced by AI.
“There will be an important place for humans for a very long time to cooperate and put the finishing touches on anything AI generates,” Janson says.
Generative AI
One of the most popular terms in artificial intelligence right now is generative AI. It refers to generating data or content, which is created through machine learning based on what a user enters. In other words, text or images produced by AI. OpenAI’s ChatGPT and Google’s Bard are examples of generative AI.
Automation
The description of human work being replaced or assisted by machines, such as robots or computers. With the advent of AI, automation is expected to pick up speed. This may include the writing of news articles or programming of software entirely or in part by AI.
LLMs (Large Language Models)
The reason that AI can write a fictional episode of Seinfeld based on the plot of Umberto Eco’s classic In the Name of the Rose in no time is LLMs. These are gigantic language models that the AI is trained in by absorbing tons of information on the internet. This allows an AI to learn to reproduce human writing by learning patterns in written copy.
Open source
Source codes make up the building blocks of the digital infrastructure. Open source software means software that is available for anyone to use. It can be read, modified and further distributed.
Source: Rise.se
