Artificial Intelligence (AI) is changing the way we live, work and interact with the world. Although there is great concern about job losses due to automation, many new jobs are also being created in AI.
• Prompt engineering, or request engineering, consists of the development of natural language processing (NLP) models and algorithms capable of understanding and responding to human language in a precise, relevant and coherent way.
• AI ethics and governance specialist: As the use of AI systems becomes more widespread, the need grows for ethics and governance professionals to ensure that systems are developed ethically and responsibly, helping organizations to navigate the complex ethical and legal issues involved in this technology, such as privacy, bias, and transparency.
• AI business strategy expert: As more companies invest in AI, the need grows for professionals who can help them develop and execute AI strategies that align with their business objectives.
• AI Product Manager: Responsible for the development and management of products and services based on this technology, AI Product Managers work with cross-functional teams to define product requirements, develop roadmaps, and ensure that products are delivered to customers. on time and on budget.
• AI UX Designer: As AI becomes more ubiquitous, the need grows for professionals capable of designing intuitive, engaging, and responsive user experiences.
• AI Cybersecurity Analyst: As AI systems become increasingly more complex, they also become more vulnerable to cyberattacks. AI cybersecurity analysts help organizations identify and mitigate AI-related security risks, such as data privacy issues, system vulnerabilities, or insider threats.
• AI engineers, responsible for creating and integrating AI algorithms into existing systems, must understand both the technical aspects of AI and the business needs of the organization they work for, while staying up to date with the latest developments. advances in this technological field AI to ensure that their systems remain competitive.
• Data scientists and machine learning specialists, meanwhile, work with large data sets to develop predictive models using algorithms that “train” AI systems to recognize and respond to specific inputs, such as images, voice or text. All of this requires a deep understanding of statistics, mathematics and computer science, as well as specific knowledge of the field in question, such as medicine, finance or engineering.
• Software developers, responsible for creating the applications and platforms that make AI work, use programming languages such as Python, Java or C++ to create the programs that allow AI to communicate, learn and make decisions.
Among the challenges facing the labor market due to advances in AI are:
• Automation: The increased use of artificial intelligence has raised concerns about the potential for job losses, especially in sectors that rely heavily on manual labor or repetitive tasks.
• Obsolescence of skills: The use of AI in companies has also caused a change in the demand for skills.
• Biases: One of the issues facing the workplace due to AI is potential bias, as AI systems are only as impartial as the data they are trained on, so if the data used to train an AI system are biased, the system will reflect those biases, which in turn can lead to discrimination in the selection and hiring process.
• Protection of the right to privacy: The use of AI in the labor market has raised concerns about the collection of personal data, as companies can collect data on candidates through online profiles, social networks and other sources, and Use them to filter candidates and make hiring decisions.
• Unequal distribution of benefits: Although AI has the potential to create new employment opportunities and improve productivity, the benefits of these advances may not be distributed equally, with some workers benefiting more than others, depending on your qualifications and the demands of your job.
Overall, the challenges facing the labor market due to advances in AI require careful evaluation and planning to ensure that the benefits of technology are distributed equitably and workers are not left behind. This may require investing in training programs that help workers acquire the skills necessary to succeed in the labor market, ensuring that AI systems.
