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Article analysis:

The article titled "Worried about AI gobbling up your job? Start doing these 3 things now" discusses the potential impact of artificial intelligence (AI) on jobs, particularly for women and highly-skilled white-collar workers. While the article raises important concerns, it also exhibits some biases and lacks certain evidence and counterarguments.

One potential bias in the article is its focus on the impact of AI on women's jobs. The author highlights a study that found 71% of jobs threatened by AI belonged to women in support roles. While this is an important issue to address, it would have been valuable to also explore the potential impact on men's jobs. The article briefly mentions that a greater share of women than men are at risk of losing their jobs due to AI, but does not provide further analysis or evidence.

Additionally, the article claims that AI will initially target high-paying white-collar jobs, particularly those held by Asian professionals. However, this claim is not supported by specific evidence or research. It would have been beneficial to include more data or studies that demonstrate which types of jobs are most at risk from AI.

The article also suggests that individuals should learn how to use AI tools and stay up-to-date on AI trends to remain relevant in the workforce. While this advice may be helpful, it does not fully address the potential challenges and inequalities that could arise from widespread adoption of AI. The article could have explored potential policy solutions or ways to ensure equitable access to training and opportunities in an AI-driven economy.

Furthermore, the article does not thoroughly examine counterarguments or alternative perspectives on the impact of AI on jobs. It primarily presents a one-sided view that emphasizes the potential risks and challenges without fully exploring potential benefits or mitigating strategies.

Overall, while the article raises important concerns about the impact of AI on jobs, it exhibits biases in its focus on women's roles and lacks comprehensive evidence and analysis. It would have been valuable to provide a more balanced perspective and explore potential solutions to address the challenges posed by AI in the workforce.