AI and the future of design: What skills do we need to compete against the machines?

AI and the future of design: What skills do we need to compete against the machines?

In a study on the future of employment by Carl Benedikt Frey and Michael A. Osborne, it was found that telemarketing is the job most likely to disappear. This brings up the question of how automation will impact various fields and what skills will be necessary to compete against machines. The study identifies three factors that determine the level of risk: perception and manipulation, creative intelligence, and social intelligence.

Occupations that involve complex perception and manipulation activities, the ability to come up with clever ideas or new problem-solving approaches, and negotiation, persuasion, empathy, and adaptability are less likely to be automated. However, recent advancements in computer vision and deep learning systems have shown that AI can deconstruct massive data sets of images and objects to inform algorithmic design. This means that perceptual activities that were once considered unique to human designers can be replaced by AI systems in the future.

Creative intelligence is another area that poses a challenge for AI technologies. Coming up with valuable ideas and solving problems requires insight, perspective, and understanding. While machines can generate countless design variations based on principles and patterns, it is difficult to imagine computers challenging themselves with creative questions and evaluating the value of their solutions.

On the other hand, jobs that require high social intelligence, such as public relations, acting, or comedy writing, are less likely to be automated in the near future. Social intelligence plays a crucial role in human-centered design, as designers need to have a deep understanding of culture and humanity. This is an area where computer science researchers have yet to make significant progress.

In a different context, the automation of reading notes has been explored. The process involves three steps: reading the book and marking it up, creating a source note for the book, and reviewing and curating the notes. Automation was initially seen as a way to save time, but it resulted in a detached and remote experience. By manually going through the process of capturing notes and curating them in Obsidian, the author found that they were able to absorb the information better and make more meaningful connections.

When capturing reading notes, it is important to wait until finishing the book before creating the notes in Obsidian. This allows for better judgment on which passages are worth capturing. Creating a source note for the book acts as a map of content and allows for transcluded links to separate notes. Sometimes, capturing a thought doesn't require a separate note and can be included in the source note itself.

In conclusion, as AI continues to advance, certain skills will be more valuable in the job market. Occupations that involve complex perception and manipulation, creative intelligence, and social intelligence are less likely to be automated. However, the combination of deep learning systems and codified heuristics may impact the perceptual activities of designers. Social intelligence and creative intelligence remain challenging areas for AI researchers. When it comes to capturing reading notes, a manual approach allows for better absorption of information and more meaningful connections. Three actionable advice for competing against machines in design and knowledge management are: 1) Cultivate skills that involve complex perception and manipulation, creative intelligence, and social intelligence. 2) Embrace the use of AI as a tool rather than a replacement. 3) Take a more hands-on approach to capturing and curating knowledge to enhance understanding and make meaningful connections.