Carnegie Mellon University has a well -deserved reputation as one of the best schools in the country for computer science. The graduates also work at large technology companies, startups and research laboratories worldwide.
Nevertheless, the faculty of the department for all its success in the past this summer is planning to reconsider what the school should teach to adapt to the rapid progress of generative artificial intelligence.
The technology has “really shaken in computer science,” said Thomas Cortina, a professor and an associated dean for the university's student programs.
Computer sciences, more than any other field, is challenged by Generative AI
The AI technology behind chatbots such as Chatgpt, who can write essays and answer questions with human fluency, runs within the academic world. But AI comes the fastest and most powerful to the computer science, which emphasizes the writing of code, the language of computers.
Large technology companies and startups have introduced AI assistants that can generate code and quickly become capable of. And in January Mark Zuckerberg, Chief Executive of Meta, predicted that AI technology would effectively agree the performance of a Midlevel software engineer somewhere this year.
Computer -scientific programs at universities throughout the country are now trying to understand the implications of the technological transformation, struggling with what to keep teaching in the AI era. Ideas vary from less emphasis on controlling programming languages to focusing on hybrid courses that are designed to inject computer use in every profession, because educators think about what the technical jobs of the future will look like in an AI economy.
“We see the tip of the AI Tsunami,” said Jeannette Wing, a professor in computer science who is executive vice -president research at Columbia University.
Increasing the feeling of urgency is a technical labor market that has been tightened in recent years. Graduates from computer science notice that vacancies, once abundant, are often scarce. Technology companies have been relying on AI for some aspects of coding, which eliminates some work at entry level.
Some educators now believe that the discipline could broaden to become more of a diploma in the free arts, with a greater emphasis on critical thinking and communication skills.
The National Science Foundation finances a program, level UP AI, to bring university and community college -educators and researchers together to achieve a shared vision of the essence of AI education. The 18-month project, run by the Computing Research Association, a non-profit organization for research and education, in collaboration with New Mexico State University, organizes conferences and round tables and produces Whitepapers to share resources and best practices.
The initiative with NSF-Stunde was made because of “a sense of urgency that we need many more computer user students-and more people who know ai at the workforce,” said Mary Lou Maher, a computer scientist and a director of the Computing Research Association.
The future of computer science, said Dr. Maher, will probably concentrate less on coding and more on computational thinking and AI literacy. Computational thinking includes breaking down problems in smaller tasks, the development of step-by-step solutions and the use of data to draw evidence-based conclusions.
AI literacy is a household name – at different depths for students at different levels – how AI works, how to use it in a responsible manner and how it influences society. Cherishing informed skepticism, she said, should be a goal.
At Carnegie Mellon, while faculty members are preparing for their meeting, Dr. Cortina that was his own opinion that the courses should include instructions in the traditional basic principles of computers and AI principles, followed by a lot of practical experience with designing software using the new tools.
“We think that's where it is going,” he said. “But do we need a deeper change in the curriculum?”
Currently, individual professors in computer science choose to have students used AI last year, Carnegie Mellon approved AI for introductory courses. Initially, Dr. said Cortina, many students considered AI as a “magical bullet” to quickly complete homework assignments, involving writing programs.
“But they didn't understand half of what the code was,” he said, so many realized the value to know how to write and debugs themselves. “Reset the students.”
This applies to many computer science students who embrace the new AI tools, with a few reservations. They say they use AI to build initial prototype programs, for checking for errors in code and as a digital tutor to answer questions. But they are reluctant to trust too much, for fear that it will make their computer insight boring.
Many students say they send 100 to 200 applications for summer internships and first jobs. Connor Drake, who will become a senior at the University of North Carolina in Charlotte next fall, counts herself happiness and has scored an interview after submitting only 30 applications. This summer he got a job as a cyber security trainee for Duke Energy, a large utility company, in Charlotte.
“A diploma of computer science used to be a golden ticket for the promised land of jobs,” said Mr. Drake, 22,. “That is no longer the case.”
Mr. Drake's personal AI Defense strategy is to expand his skills. In addition to his computer science, he brought in political sciences with a specialty in security and intelligence studies – a field where his expertise in cyber security could be applied properly. He is president of a university cyber security club and has served in the student government.
Like other computer science students, Drake is forced to adapt to an increasingly difficult technical labor market. Various factors, say labor experts, are at work. Large technology companies in particular have limited their recruitments in recent years, a sharp withdrawal of the tree years from the Pandemic era. The exception is the hectic recruitment of a relatively small number of the most coveted AI experts, who are offered lucrative wage packages.
But most technology workers do not work for technology companies. The general employment for employees in technical professions had generally stopped until recently – according to government statistics since February has fallen by 6 percent since February.
Employers have sent a sharper signal with a considerable withdrawal into technical vacancies. In the past three years there has been a decrease of 65 percent of companies looking for employees with two years of experience or less, according to an analysis of Comptia, an organization for technology research and education. The decrease in offers for technical employees with all experience levels has fallen by 58 percent.
“We mainly see a postal Pandemic rejection of recruitment and the impact of the current economic uncertainty,” said Tim Herbert, Chief Research Officer at Comptia. “We don't really have a clear AI effect yet.”
Although the road is perhaps uncertain for computer science education, the market for AI-assisted software is ready for growth, experts say. AI is a productivity tool, and every new wave of computers – the personal computer, the internet, the smartphone – has increased the demand for software and programmers.
This time, they say, the result can be an eruption of technology democratization, because tools in chatbot style are used by people in areas of medicine to marketing to make their own programs, tailor-made for their industry, fed by industry-specific data sets.
“The growth in software engineering jobs can fall, but the total number of people involved in programming will increase,” says Alex Aiken, a professor of computer science at Stanford.
