Humanistic understanding of AI, generalists thrive in the field. AI Engineer role
Creativity and soft skills become more valuable than ever. AI continues to reshape industries and redefine the nature of work, those with a broad understanding of both technology and human nature will lead this evolution. A comprehensive general understanding is the success factor, to decide on what tools building your solution based on quality input and output.
Human ideation and machine execution creates a powerful feedback loop, enabling faster and more natural interactions than ever before; therefore, faster product iterations.
Learning with human drive
While AI excels at processing vast amounts of data at lightning speed, the real magic happens when human insight and creativity enter the equation. Effectiveness and efficiency of those techniques come from the right teaching and learning. Those who are the most capable to teach and explain their requests are the ones who will get the most value out of this technology.
The work and input of a smart person is of use to:
- Choose the right model, choose the right training techniques.
- Provide the right data for the specific sought result.
- A slight view and fast quality control on the results.
Those who learnt and understand human nature are at a position of taking advantage of AI as much as highly technical individuals.
At businesses
AI can be super cheap to apply for less than 10 Euros, or super costly and unbearable for most small enterprises. It really depends on the right guidance, while at some point past technological improvements were disregarded due to costs, AI should be assessed for its use, set whatever budget and do research. It is a must to assess how to implement AI at your processes, target small scale improvements.
- Small businesses can now perform at rates previously reserved for larger companies.
- Rapid prototyping and experimentation become more accessible.
- Obtain insights from your data, without a dedicated team.
AI engineer figure
The role that synthesises all these general skills is called an AI engineer. Characteristics required to develop AI projects, to be an AI engineer:
- Assess pre-built components, stay updated with latest advancements.
- Arranging those components together to create practical business applications.
- With the responsibility to build and deploy AI systems, a reliable infrastructure.
- Soft Skills: creativity, communication, emotional intelligence, critical thinking.
- Hard skills: ML programming, cloud computing, and distributed systems.
The more intelligent the artificial intelligence the more we can refocus from hard skills and technology to humans.
