ChatGPT's Deep Research just identified 20 jobs it will replace. Is yours on the list? - Related to deep, may, releases, worldwide:, a

ChatGPT's Deep Research just identified 20 jobs it will replace. Is yours on the list?

This week, OpenAI launched its Deep Research feature which can synthesize content from across the web into one detailed analysis in minutes leveraging a version of the corporation's latest model, o3.

This feature is a powerful tool for workers, as it can save them hours by completing research autonomously. But can the technology's underlying model replace workers? Yes, hints at Deep Research.

Also: Don't want to pay for ChatGPT Deep Research? Try this free open-source alternative.

Min Choi, an X user whose account is dedicated to sharing informational AI content, asked Deep Research to "List 20 jobs that OpenAI o3 reasoning model will replace human with into a table format ordered by probability. Columns are Rank, Job, Why more effective Than Human, Probability." Choi then shared the results of the chat via an X post, which has since garnered 984,000 views:

After deep diving into 24 data in seven minutes, the X post exhibits that Deep Research produced a table that included job titles, explanations as to why an AI is superior than a human at the role, and the probability that the job will be replaced. Choi shared a link to the entirety of its interaction, which you find here to see the table in detail.

Right in time with tax return season, leading the table was the role of "tax preparer" with a probability of 98% replacement, which ChatGPT deemed as "near-certain automation".

ChatGPT explained that AI would be superior at the task because it can quickly process tax rules and calculations, which would make it faster than a human. To support its argument, ChatGPT highlighted that AI-driven tax software already exists.

The rest of the professions cited on the list included in order were: data entry clerk, telemarketer, bookkeeper, paralegal, appointment scheduler, virtual assistant, transcriptionist, proofreader, copywriter, customer service representative, email marketer, content marketer, social media manager, translator, technical support analyst, recruiter, market research analyst, travel agent, and tutor.

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All of the jobs that ChatGPT suggested have an underlying theme in common: the role mostly relies on a technical skill that AI can do well autonomously. For example, AI can transcribe, translate, and proofread effectively, making the need for humans to perform these job's hard skills less imperative.

Another thing AI can do well is analyze a robust amount of materials, draw conclusions, and even perform actions based on its own analysis. Therefore, roles with that process at the center of their responsibilities, such as social media manager, recruiter, travel agent, market research analyst, appointment scheduler, bookkeeper, and paralegal, are deemed more in danger.

Does this research mean everyone in these fields is going to lose their job? No, this outcome is highly unlikely. The analysis by ChatGPT only accounts for AI's ability to perform the hard skills effectively. However, soft skills, including communication, critical thinking, conflict resolution, leadership, time management, and interpersonal skills, are equally as essential to success -- and AI can't replicate those capabilities.

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Furthermore, organizations are not yet ready to widely adopt AI. For example, a recent Accenture study showed that there are still many obstacles preventing business leaders from widespread implementation of AI in organizations, such as lack of clarity on return on investment, infrastructure limitations, and disconnection from employees.

If you want to ask Deep Research a similar question or dive deep into another topic, you will need to get a $200-per-month ChatGPT Pro subscription. Although the price is steep, the subscription includes other perks, such as unlimited access to ChatGPT and Sora, and access to Operator, its AI agent feature that can carry out basic browser-based tasks, like reservations.

There are also some lower-cost alternatives, such as Google's Deep Research feature, which is available to all Gemini Advanced customers through the Google One AI Premium plan that costs $20 per month, or Hugging Face's newly released equivalent, also called Deep Research, which is free to demo.

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OpenAI's Sora generates 600 videos a minute worldwide: Top 5 cities may surprise you

Video creation is still the frontier of generative AI, and OpenAI leads the pack with its Sora AI video generator. The generator, which launched last month during the 12 days of OpenAI, has caused quite a buzz because of its highly realistic output quality.

On Wednesday, OpenAI shared with ZDNET that there are 10 Sora generations per second worldwide. That translates to 600 videos being generated every minute. The top five cities for Sora adoption are Seoul, New York City, Tokyo, Los Angeles, and Singapore, listed from highest to lowest.

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With Sora, creating a video from scratch is as easy as dropping in a prompt or an existing asset you own, such as an image or video in your gallery. You can also customize ratios, duration, and even select from presets to get your creative juices flowing.

Beyond video, OpenAI shared that the second-fastest growing feature on Sora is remixing, which allows people to add, remove, or edit objects in an existing video by using a text prompt, as seen in the video below. When remixing, people are also able to select the strength of the remix, depending on how much of the original video's essence they want to keep.

Sora also offers other video editing attributes, such as re-cut, which lets customers trim and extend existing clips, and blend, which transitions elements from one video to another. Both Sora's video editing and generating attributes have practical applications for content creators and working professionals who could benefit from using the platform to create b-roll, marketing video materials, clips, and more.

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Google releases responsible AI report while removing its anti-weapons pledge

The most notable part of Google's latest responsible AI research could be what it doesn't mention. (Spoiler: No word on weapons and surveillance.).

On Tuesday, Google released its sixth annual Responsible AI Progress research, which details "methods for governing, mapping, measuring, and managing AI risks," in addition to "updates on how we're operationalizing responsible AI innovation across Google."

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In the findings, Google points to the many safety research papers it (more than 300), AI education and training spending ($120 million), and various governance benchmarks, including its Cloud AI receiving a "mature" readiness rating from the National Institute of Standards and Technology (NIST) Risk Management framework.

The research focuses largely on security- and content-focused red-teaming, diving deeper into projects like Gemini, AlphaFold, and Gemma, and how the enterprise safeguards models from generating or surfacing harmful content. It also touts provenance tools like SynthID -- a content-watermarking tool designed to advanced track AI-generated misinformation that Google has open-sourced -- as part of this responsibility narrative.

Google also updated its Frontier Safety Framework, adding new security recommendations, misuse mitigation procedures, and "deceptive alignment risk," which addresses "the risk of an autonomous system deliberately undermining human control." Alignment faking, or the process of an AI system deceiving its creators to maintain autonomy, has in the recent past been noted in models like OpenAI o1 and Claude 3 Opus.

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Overall, the findings sticks to end-user safety, data privacy, and security, remaining within that somewhat walled garden of consumer AI. While the findings contains scattered mentions of protecting against misuse, cyber attacks, and the weight of building artificial general intelligence (AGI), those also stay largely in this ecosystem.

That's notable given that, at the same time, the corporation removed from its website its pledge not to use AI to build weapons or surveil citizens, as Bloomberg reported. The section titled "applications we will not pursue," which Bloomberg reports was visible as of last week, appears to have been removed.

That disconnect -- between the findings's consumer focus and the removal of the weapons and surveillance pledge -- highlights the perennial question: What is responsible AI?

As part of the research announcement, Google expressed it had renewed its AI principles around "three core tenets" -- bold innovation, collaborative progress, and responsible development and deployment. The updated AI principles refer to responsible deployment as aligning with "user goals, social responsibility, and widely accepted principles of international law and human rights" -- which seems vague enough to permit reevaluating weapons use cases without appearing to contradict its own guidance.

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"We will continue to focus on AI research and applications that align with our mission, our scientific focus, and our areas of expertise," the blog notes, "always evaluating specific work by carefully assessing whether the benefits substantially outweigh potential risks."

The shift adds a tile to the slowly growing mosaic of tech giants shifting their attitudes towards military applications of AI. Last week, OpenAI moved further into national security infrastructure through a partnership with US National Laboratories, after partnering with defense contractor Anduril late last year. In April 2024, Microsoft pitched DALL-E to the Department of Defense, but OpenAI maintained a no-weapons-development stance at the time.

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