ChatGPT Will KILL These Tech Jobs: Avoid These Tech Roles If You Can | Tech Jobs Replaced By AI

Tech with Luca
8 Apr 202306:27

TLDRIn this video, the speaker discusses the most at-risk tech jobs due to advancements in AI and chatbot technologies like GPT and copilot. Roles such as QA testers, non-programming data scientists, technical leads, cloud engineers, and internal tool developers may see their responsibilities reduced or become obsolete. However, highly technical fields like full-stack mobile development, AI, and machine learning remain in high demand, as the human element is still crucial for ensuring coherence and quality in tech projects.

Takeaways

  • 🤖 QA Testing roles are at high risk due to advancements in AI like chatbots, which can streamline the test case generation process.
  • 🔄 Test engineers may need to reconsider their career paths as AI technologies might eventually merge testing responsibilities into software engineering roles.
  • 📉 Non-programming data science roles focusing on data analysis may be at risk, as AI can process and interpret data, reducing the need for large non-technical teams.
  • 🧠 Data scientists who build models or engage in more technical tasks are less likely to be replaced by AI, as their expertise remains crucial.
  • 🏗️ Tech leads and architects might see their roles evolve as AI technologies can take over some of their responsibilities in creating design patterns.
  • 🌐 Cloud engineering roles that involve customer onboarding and API setup may be diminished as AI-driven tools enable self-service environments.
  • 🔧 Internal tooling roles could face shifts as companies may opt for AI-enhanced productivity tools or B2B products over custom solutions.
  • 📱 Full stack mobile development and specialized fields like AI and machine learning remain in high demand, requiring technical skills that AI cannot replace yet.
  • 👥 Human elements in tech roles are still necessary for ensuring coherence and making sense of AI-generated outputs.
  • 🚀 New roles will likely emerge to bridge the gap between AI technologies and user experience, but the specifics remain uncertain.

Q & A

  • What does the speaker believe is the most risky tech job in the context of emerging technologies?

    -The speaker believes that QA testing, specifically the role of test engineers, is the most at risk due to the introduction of technologies like chat DBT and co-pilot, which can streamline the process of generating test cases and potentially make the human factor almost obsolete.

  • How might the role of software developers be affected by the advancements in AI and automation?

    -Software developers may take on additional responsibilities, such as end-to-end unit testing and smoke testing, as AI technologies can aid in these tasks. This could lead to a merging of testing roles into the overall software engineering job.

  • What is the potential impact on non-programming roles in data science?

    -Non-programming roles in data science, such as those focused on analyzing and making sense of data without building models, may be at risk. With AI and machine learning advancements, these roles could be streamlined and potentially reduced, as AI can help generate insights and present them in a human-readable format.

  • How might the introduction of AI technologies affect the role of technical leads and architects?

    -Technical leads and architects may see their roles combined with AI technologies, as these tools can provide design patterns and knowledge that can help onboard new team members faster. This could reduce the need for dedicated technical leads in some cases.

  • What changes are expected in cloud engineering roles with the advent of AI tools?

    -Cloud engineering roles that involve customer onboarding and API setup may be replaced by AI-generated tools. Customers could potentially set up their own cloud instances without needing human assistance, reducing the need for entry-level cloud engineers.

  • How can internal tooling roles be affected by the rise of AI and specialized B2B products?

    -Internal tooling roles may shift as companies focus on building tools for developer productivity or adopt specialized B2B products like co-pilot. This could lead to smaller teams and a greater reliance on AI technologies for internal software engineering tasks.

  • What tech fields are still considered important and in high demand according to the speaker?

    -Full stack mobile development, artificial intelligence, and machine learning are considered important and in high demand fields that require specialized technical skills.

  • How do project management (PM) and user experience (UX) roles stand to benefit from AI technologies?

    -PM and UX roles may use AI technologies to assist in their day-to-day tasks, improving efficiency and productivity. New tools and technologies will likely be developed to bridge the gap between these roles and the evolving tech landscape.

  • What advice does the speaker give to those considering a career in tech?

    -The speaker advises that while many roles may be affected by AI and automation, technical skills remain crucial. They suggest focusing on specialized fields like AI and machine learning, and being aware of the potential shifts in job roles due to emerging technologies.

  • How does the speaker suggest the human element will continue to play a role in tech jobs?

    -The speaker emphasizes that while AI can generate code and streamline processes, the human element is still necessary to ensure that everything makes sense and follows the correct patterns. Human oversight and creativity will continue to be important in tech roles.

Outlines

00:00

🔍 The Riskiest Tech Jobs in the Age of AI

This paragraph discusses the impact of AI technologies, particularly chatbots and GPT (Generative Pre-trained Transformer), on various tech jobs. The speaker, Luca, identifies Quality Assurance (QA) testing as the most at-risk role due to the automation of test case generation. The video also touches on the potential obsolescence of non-programming roles in data science, as AI can streamline data analysis. The speaker suggests that software developers may need to take on additional testing responsibilities, and that tech leads may become less necessary as AI can provide design patterns and guidance. The paragraph ends with a note that while AI is transforming the tech landscape, human elements are still crucial for the foreseeable future.

05:00

🚀 Safe Tech Roles and the Future of AI in Tech

In this paragraph, Luca continues the discussion on the impact of AI on tech jobs, focusing on roles that are less likely to be replaced by AI. Full stack mobile development and specialized fields like artificial intelligence and machine learning are highlighted as being in high demand. The speaker also mentions that project management, UX, and other non-technical roles may adapt by utilizing AI tools to enhance their day-to-day tasks. The paragraph concludes with a reminder that while AI is introducing new tools and changing job roles, it's essential for professionals to stay informed about the evolving tech landscape, especially in internal tooling and cloud engineering, to ensure their roles remain relevant and valuable.

Mindmap

Keywords

💡Tech job

A tech job refers to a profession within the technology industry, which can range from software development to data analysis and cloud computing. In the context of the video, the speaker discusses the potential risks and changes to various tech jobs due to the advent of AI technologies like chatbots and GPT (Generative Pre-trained Transformer models).

💡QA testing

QA stands for Quality Assurance, and QA testing is the process of evaluating a product or service to ensure it meets certain standards and functions as expected. In the video, the speaker suggests that AI technologies could streamline the test case generation process, potentially reducing the need for human QA testers.

💡AI technology

AI, or Artificial Intelligence, refers to the development of computer systems that can perform tasks typically requiring human intelligence, such as learning, reasoning, and problem-solving. The video discusses how AI technologies, particularly chatbots and GPT models, are transforming various tech roles by automating certain tasks and changing job responsibilities.

💡Data science

Data science is a field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data. In the video, the speaker points out that non-programming roles in data science, such as those focused on data analysis without model building, could be at risk due to AI's ability to process and interpret data more efficiently.

💡Software engineer

A software engineer is a professional who applies engineering to the design, development, maintenance, and testing of software systems. In the context of the video, software engineers may need to take on additional responsibilities, such as end-to-end testing, as AI technologies become more integrated into their roles.

💡Cloud engineering

Cloud engineering involves the design, build, and management of cloud computing solutions, which allow for the delivery of computing services over the internet. The video discusses how AI tools could replace certain cloud engineering roles, such as those focused on helping customers set up and use APIs.

💡Technical architect

A technical architect is a professional who designs and oversees the implementation of IT architecture within an organization. They are responsible for creating design patterns and ensuring that technology solutions align with business goals. In the video, the speaker suggests that the role of technical architects may evolve as AI technologies become more prevalent, potentially reducing the need for human architects in some cases.

💡Internal tooling

Internal tooling refers to the software tools and systems that a company develops for its own internal use, to improve efficiency, productivity, or other aspects of its operations. In the video, the speaker discusses how the focus on internal tooling may shift, with companies potentially relying more on AI-powered B2B products rather than building custom tools.

💡Full Stack mobile development

Full Stack mobile development refers to the process of developing both the front-end (user interface) and back-end (server, database, and application logic) of mobile applications. In the video, it is suggested that despite the changes brought by AI, full stack mobile development remains an important and in-demand field within the tech industry.

💡Artificial Intelligence (AI)

Artificial Intelligence, or AI, is the simulation of human intelligence in machines that are programmed to think and learn like humans. In the video, AI is presented as a transformative force in the tech industry, with the potential to automate and enhance various tasks, leading to shifts in job roles and responsibilities.

💡Machine learning

Machine learning is a subset of AI that focuses on the development of algorithms and statistical models that allow computers to learn from and make predictions or decisions based on data. In the video, machine learning is mentioned as a specialized field that requires technical skills and is in high demand, indicating its importance and resilience to the changes brought by AI technologies.

Highlights

The most risky Tech job discussed is QA testing due to the introduction of technologies like Chat DBT and co-pilot.

Test engineers who write texts and help make features work correctly are at a higher risk due to automation.

The human factor in testing may become obsolete as AI technologies streamline the process.

Software developers can expect to take on additional responsibilities in testing, including end-to-end, unit tests, and smoke tests.

Non-programming roles in data science, such as pure data analysts, are at risk due to AI's ability to process and analyze data.

Data scientists may no longer need a team of non-technical data scientists, as AI can generate human-readable formats and frameworks.

Tech leads and architects may see their roles combined with AI technologies, reducing the need for dedicated personnel.

Cloud engineering roles that involve customer onboarding and API setup may be replaced by AI-generated tools.

Sales and Post-Service Engineers will still be needed, but entry-level cloud roles may become less available.

Internal tooling roles may shift as companies focus on building tools for developer productivity or adopt B2B products like co-pilot.

Full stack mobile developments and specialized fields like AI and machine learning remain in high demand.

Technical skills are still crucial as computers can generate boilerplate code but not replace the human element.

PM roles and UX designers will also utilize AI technologies to assist in their day-to-day tasks.

New roles will be created to fill the gap between UX and the new tools provided by AI technologies.

The impact of AI technologies on various tech roles is significant, and professionals should be aware of the changes.

The video aims to provide insight into career choices in the face of evolving AI technologies.

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