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\t\t\tIllustration by Tag Hartman-Simkins \/ Futurism. Source: Getty Images<\/p>\n
Graduates at some of the top universities are finding it nearly impossible to find new jobs in software engineering. <\/p>\n
New reporting by the Los Angeles Times<\/a> details the trouble recent graduates are having finding entry level jobs \u2014 even those with degrees from vaunted institutions like Stanford University.<\/p>\n \u201cStanford computer science graduates are struggling to find entry-level jobs\u201d with the most prominent tech companies, Stanford bioengineering professor Jan Liphardt told the LA Times. \u201cI think that\u2019s crazy.\u201d One Stanford student, who spoke to the paper anonymously, said that \u201cthere\u2019s definitely a very dreary mood on campus.\u201d<\/p>\n As the newspaper describes it, a prevailing idea among those at either end of the software hiring pipeline is that for every ten programmers, companies now only need two, plus a large language model (LLM). <\/p>\n \u201cThe AI now can code better than the average junior developer that comes out of the best schools out there,\u201d Amr Awadallah, CEO of Palo Alto-based AI startup Vectara, bragged to the paper. \u201cWe don\u2019t need the junior developers anymore.\u201d<\/p>\n To cope with the difficulty in finding entry-level jobs, recent graduates from what you\u2019d think of as elite universities are taking jobs with companies they might once have perceived as beneath them, the paper notes. Others are going the long route, either by founding their own startups to compete for a piece of the venture capital pie<\/a> or by signing on for graduate degrees to bolster their resumes.<\/p>\n Yet as compsci grads struggle to find jobs in this strange new world, research suggests AI isn\u2019t technically ready to take the hot seat. One study from earlier this year found that when software developers use AI tools to code, it actually makes them 19 percent slower<\/a>. That result was the complete opposite of forecasts by economics experts, machine learning experts, and even the developers themselves \u2014 in short, the dominant narrative pushed by both AI boosters and AI doomers<\/a>.<\/p>\n There\u2019s also a strange contradiction playing out between the reality on the ground and the data coming out of the labor market.<\/p>\n Another research report<\/a> by the investment company Vanguard found that the top 100 occupations most exposed to automation by AI are in reality outperforming the rest of the labor market, both in terms of wage and job growth. \u201cThis suggests that current AI systems are generally enhancing worker productivity and shifting workers\u2019 tasks toward higher-value activities,\u201d reads the report.<\/p>\n The fact that this productivity shift isn\u2019t translating into prosperity for more people suggests that blame doesn\u2019t fall on AI itself, but on the economic system governing its use. As technology analyst Morten Rand-Hendriksen explains<\/a>, \u201cAI can\u2019t replace people, but it can create short-term financial gain at the cost of long-term skill- and knowledge loss.\u201d<\/p>\n \u201cThat\u2019s what we\u2019re seeing here, and that\u2019s what should worry us,\u201d Rand-Henriksen continues. \u201cAI in all its forms can be a tool to extend our capabilities, but that requires leaders and an economic environment that values human work and human gains over increasing shareholder profits. AI is an exponentially replicating canary in the coalmine of capitalism. If we don\u2019t act now to make room for ourselves, not only the air but the space will run out.\u201d<\/p>\n