Three climate challenges facing the alcoholic…
Heka.ai, the AI & Data Science ecosystem of Sia Partners presents its analysis of Artificial Intelligence trends for 2022-2023, covering technological, organizational and societal issues.
After wide adoption by digital giants (GAFAM), artificial intelligence is now being democratized by smaller companies as well as start-ups that are able to seize its potential to develop innovative products and services in many sectors such as energy or health.
In the energy sector, the implementation of intelligent sensors has made it possible to meet the challenges of predicting consumption, predictive maintenance and customer knowledge.
The Insurance sector, which is already mature in terms of data, uses data to predict customer behavior for fraud detection and churn prevention.
The healthcare sector, at the very heart of AI expansion, is now adopting computer vision techniques for the early diagnosis of metastases and other diseases.
The number of publications dealing with AI has increased dramatically over the past 10 years and major powers, including China, the European Union and the United States, are rushing to heavily invest in AI research. The rise of AI conferences also plays a fundamental role in the dissemination of research and scientific communications, thus contributing to data acculturation within companies, schools and the general public. AI is today catalyzed by fundamental research and vice versa, research is also shaken up by AI, which allows revolutionary applications, such as within drug design, with new modeling techniques that are increasingly efficient.
The growing demand for AI-skilled profiles on the job market is also prompting educational institutions to adapt their academic curriculum, coupled with a real democratization thanks to online training and communities, which are catalysts for the development of new talents
The capabilities of artificial intelligence have evolved at a rapid pace in recent years. What seemed impossible until recently is now taken for granted. This is the case, for example, of the AlphaFold prowess developed by DeepMind, which can predict the structure of proteins, a major contribution to biology research.
To support these algorithmic breakthroughs, an entire technological ecosystem is thriving, with the massive adoption of cloud in particular, but also a human environment that is constantly being challenged. The gradual appropriation of AI in companies implies not only a rethinking of the way projects are conducted, and a change in the corporate culture, but also the changing ways in which talents with very specific expertise are recruited.
There is no longer any doubt that artificial intelligence will occupy a central place in tomorrow's world and that it is a technology of public utility. Nevertheless, it is still perceived by many as a vector of risk, particularly in regards to violations of privacy by various actors, both public and private. It is therefore becoming vital for governments to take the lead in supporting and regulating the future development of this technology.
A framework is therefore gradually taking shape, particularly in Europe, with the implementation of the AI Act, which is in line with GDPR. This regulation aims to categorize and then frame AI applications according to their level of risk.
Similarly, some AI applications respond directly to the ethical and societal issues of the 21st century. For example, it enables an increase in the moderation capacity of social networks by detecting illegal content or harassment in real-time, among millions of posts, comments and messages.
States, therefore, have the responsibility to expand their framework in order to allow it to bring as much value as possible without becoming a societal or environmental risk factor.