Parallelisms

By Eva bruch
TWITTER @evabruch

The parallels are interesting. On the one hand, they can provide early warning signs of unwanted situations. For example, the crash of 1929 and the financial crisis of 2008. Both crises were preceded by an anomalous financial period (uncontrolled speculation in the first case and a real estate bubble in the second), an excessive expansion of credit and lack of specific regulation in the markets in both cases. Although despite the signs, we rarely pay attention to them.

On the other hand, they help us reflect and gain perspective on situations that may not be completely understood in the present and that generate anxiety about the future. The introduction of email and the Internet at the time generated mixed feelings, a paradigm shift that put some services and jobs at risk. The same thing happened with the electric telegraph many years before. But both innovations led to an acceleration of trade and communications, cost savings and global economic growth.

Another parallel is that of the industrial revolution with the digital revolution. Major changes in the first made it possible to move from an agrarian economy to an industrial one, generating massive urbanization and changes in working conditions. The digital revolution marked the birth of the digital economy, the creation of new industries, new jobs and profound changes in communication and information. But both were accompanied by important challenges: job displacement, automation, privacy and cybersecurity problems... although the balance of both has been positive, even though the second has not finished.

The latest twist in this digital revolution is generative AI and intelligent machines, potentially capable of replacing people in a wide range of activities. The figures are scary. In 2017 McKinsey anticipated that automation could displace between 75 and 375 million workers by 2030. Last year The World Economic Forum indicated that around 40% of all work hours could be affected by generative language models like ChatGPT. Also in the opposite direction, as a 23% growth is expected in the demand for STEM jobs by 2030.

There are also now mixed feelings about the future impact on society, employment and security that these innovations will entail. But if we use parallels and take perspective on the situation, we can identify at least three things. The first, that evolution is not going to stop, the second, that specific regulation is needed and the third, that the balance tends to be positive (and there are several theories that support it, such as that of compensation) but that jobs will be lost and inequalities will be generated. Governments have a great responsibility in this scenario, but so do companies, which will not be able to prevent the erosion of jobs but will be able to mitigate its effects while contributing to their own strengthening.

It is possible to adopt Generative AI responsibly, IBM is doing it to improve efficiency in talent management and customer service and implementing reskilling and upskilling programs helping its employees acquire new skills and adapt to roles that require advanced AI knowledge. Deloitte use AI to analyze large amounts of data and offer more precise advice and invest in continuous training of your staff, ensuring that employees can adapt to technological changes. Procter & Gamble (P&G) employ AI to predict product demand and optimize production and implements training programs for its workers in the use of new technologies.

It is important to learn from the past, from the cycles we have experienced, review the lessons and prepare for the new future. Parallels can help in this, we have gone through similar cycles, similar situations, we have faced the same fears before, the fear of the unknown, of radical change, the need to adapt... What changes is that we can anticipate, mitigate the effects adverse events and prepare for change. The moment is now. We must take responsibility and companies have a very important role in this.