{Hi ChatGPT! Please write an article about artificial intelligence in the modern working environment.}
It probably would have taken us less than five minutes to enter this command into perhaps the world’s best-known generative AI tool and get an article about artificial intelligence and New Work back, ready to print. But is that really the future of the world of work? Where is AI going to be used, or perhaps even take over? What are the risks? And are we going to become something more akin to colleagues?
AI research – the status quo.
Almost all of us see the rapid development in the field of AI as something unfamiliar and unusual. Up to now, digital- and machine-based support in our working environments has been limited to assistance systems – the actual implementation and decision-making still left to us humans. Artificial intelligence systems, on the other hand, are becoming more and more far-reaching, working largely independently of us, and generally only requiring human intervention as the exception, rather than the rule. AI enables machines to imitate human cognitive abilities – such as logical thinking, learning and planning – by recognising and analysing the data it is fed and drawing conclusions from it. It is therefore not “intelligent” in a human sense, and cannot magically acquire a human level of understanding; the data AI works with is provided by humans, after all. At a base level, it’s all a matter of statistics.
But where are we with AI research at the moment? Markus Manz and Lukas Fischer from the Software Competence Center Hagenberg know the answer. “Research in the field of artificial intelligence is diverse, dynamic, and revolutionising a huge range of sectors and roles, including pattern recognition, forecasting, selection processes, chatbots and medical technology. Deep learning and neural networks – both sub-domains of artificial intelligence – are dominating here. Advances in the neural network architectures have revolutionised some areas of application, such as image recognition and language processing. As well as exploring new opportunities, researchers are also concentrating on making AI systems more robust, reliable and adaptable”, says Manz.
AI joins the team.
What exactly does that mean for the world of work, and where can we make best use of artificial intelligence systems? “AI is particularly suited to tasks that are repeatable and require large volumes of data. Making decisions based on complex facts, and the ability to react to changes, are also areas where AI shines”, explains Fischer. But it’s not suited to every task. “Creativity, emotional intelligence and deep interpersonal
communication are all areas where AI is (currently) lacking”, adds Fischer. If artificial intelligence is used to process complex data or perform repetitive, routine tasks, teamwork is essential – just as it is between human colleagues. “For humans and AI to develop a successful working relationship, there needs to be a clear assignment of roles, transparency, explainability, feedback loops, continuous learning, trust, and consideration of ethics and responsibility. If these basic principles and proven methods are adhered to, humans and AI can solve complex problems together”, says Manz, confidently.
Dangers and risks.
As much as AI can support and simplify our working lives, critics are constantly voicing their concerns about the dangers and risks. “There are clearly some potential dangers to be aware of when working with AI. Risks such as bias (stereotyping) and discrimination, loss of jobs and social inequality, security and data protection. There is also a potential loss of control, and many ethical questions. It’s already making our lives easier in some areas to such an extent that we could start to lose certain skills down the line”, warns Manz. The fear of losing jobs is a particularly hot topic right now. “It’s a justified concern, and the question needs to be asked. History shows that technological developments can lead to a loss of jobs in certain sectors. However, it also shows that new ones are always being created. And that’s what will happen with AI. It’s important to take potential impacts on the job market seriously and put appropriate measures in place to get the most out of the opportunities AI affords us”, explains Fischer.
Explainability and ethics are becoming increasingly important as AI starts to permeate our daily lives. The systems have to become more transparent and interpretable to ensure that AI decisions are traceable and ethically justifiable. “To this end, as part of the EU’s Digital Strategy, the EU Commission has put the Artificial Intelligence Act (AIA) in motion; a law that – in its current version – contains specific recommendations as to how research institutions and the wider business world should use AI”, explains Manz.
Effective collaboration? Ethical problems? Critical voices? Where do the experts land when it comes to collaboration with artificial intelligence systems in the workplace? “The fact is that a team of people working with AI delivers better results than the most talented people or most advanced algorithms alone. At the end of the day, whether we take advantage of artificial intelligence-based support in day-to-day working life depends on the specific requirements and objectives of a task, and the available resources and limitations. And, in the end, that can only be decided by a human.”
About Software Competence Center Hagenberg.
The Software Competence Center Hagenberg (SCCH) is a non-academic research centre that has built up a reputation for outstanding application-oriented research in the fields of data and software science over the past 25 years. This focus enables it to effectively implement projects in the fields of digitalisation, Industry 4.0 and artificial intelligence. The SCCH sees itself as an interface between the international research community and the domestic economy, and carries out world-leading research with its 130-strong team. www.scch.at
- Markus Manz is the CEO of the SCCH and is responsible for the institution’s strategic planning. He wants to further expand its collaboration with the scientific and economic community, and increase the centre’s visibility on the global stage as a world-leading institution.
- Lukas Fischer is the SCCH’s Research Manager for Data Science, and has many years of experience in research and project management.