70 - Future Skills and Abilities - Professionals of the future need to adopt more flexibility in how they work.
This means meeting people where they are at, engaging with them over social media or other more preferable platforms (Susskind 2015, pg 106). Imagine being able to instant message your doctor.
Future professionals will need to be able to take advantage of the increase and availability of data to come to insights. This involves both the collection and analyzing of data. Either the professionals themselves will work directly with the data or use a middle man that understands both the data and industry (Susskind 2015, pg 107). They will also need to get better at working with new and emerging technology. Those who can effective work alongside machines will see an increase in efficiency and effectiveness (e.g. Advanced Chess).
The final need is for workers to widen their tool set, either through the effective use of technology or introducing a multi-disciplinary approach (Susskind 2015, 108-109). Imagine a “self-help coach” but who has extensive training, such that they work with doctors and psychologists. Taking a more holistic approach to fixing oneself.
71 - Future Roles In the book The Future of the Professions: How Technology Will Transform the Work of Human Experts, author Richard Susskind lays out 12 different roles that will emerge from a “post-professional society”:
Craftspeople - people who “craft” stuff that require a difficult skill set, such that they can’t be easily replaced by para-professionals or crowd sourced.
Assistants - people who aren’t experts but help out the above mentioned craftspeople (e.g. associates in law firms).
Para-professionals - will take over the spot of experts with the help of ever increasingly competent systems and tools.
Empathizers - people with extremely good people skills, which will always be important because we have a sociality that is ingrained in our evolutionary biology. Machines will fill the gap, but people who can afford the help of other people will prefer doing so.
R&D Workers - research and development will always be desired for the creation of new technology that can allow for a greater reach of solutions or make them more effective.
Knowledge Engineers - people who will be designing systems that draw on the sources of existing expertise to disseminate knowledge to the wider public and para-professionals. Early examples may be wikipedia or thoughtCo.
Process Analysts - will be the ones deconstructing the work of experts to create the systems and tools used by the above mentioned para-professionals.
Moderators - people with deep insight who will help guide the centralization of expertise knowledge either from the masses or a pool of experts. Essentially making sure the quality of “the body of knowledge” stays high.
Designers - People who think up and design the various systems described above. If a service or system isn’t well made then people aren’t going to want to use it. You see this with the high salary and importance of UX designers.
System Providers - people who are actually providing the systems that the knowledge base is built on, whether it be a foundation (e.g. Wikipedia) or a private company (e.g. Quora).
Data Scientists - pretty straight forward field. People who are able to work with big data and come to insights. Two of my data related products are pudding.cool and quid.
Note on the source - I actually own this book and took notes on it. But because I suck and didn’t have a zettelkasten at the time, I have no clue where those notes actually are. One of the helpful layers of structure of the zettelkasten is the centralization of notes.
A good question is how well his argument still holds up 4 years later? Something to think about.
Further planned Research:
The Future Is Faster Than You Think: How Converging Technologies Are Transforming Business, Industries, and Our Lives - 2020
The Inevitable: Understanding the 12 Technological Forces That Will Shape Our Future - 2017
Humans Are Underrated: What High Achievers Know That Brilliant Machines Never Will - 2016
Rise of the Robots: Technology and the Threat of a Jobless Future - 2016
The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant - 2016
Average Is Over: Powering America Beyond the Age of the Great Stagnation - 2013
74 - Creation of Knowledge - There are two different ways I think about the creation of knowledge, a private and public way.
The first is the private creation of knowledge, which is essentially learning. It means taking information and going through the memory process, which turns it into knowledge. This can be done on a shallow level, which is necessary but not sufficient (spin off into 17b1 #todo). In contrast, when done correctly, you are going one step further and structure building with the information.
The second way is the public creation of knowledge, which encompasses cutting edge research and the remixing/rethinking of ideas. The remixing of ideas can take the form of synthesizing existing knowledge (e.g. Ryan Holiday’s Notebox, Mark Manson, etc - what I’d call the remix genre) or reformulation of existing knowledge. The later is typically done in educational settings, with articles and blog posts.
Creation of knowledge is on of the pillars that cognitive skills (17f) are geared towards (e.g. critical, creative, and three dimensional thinking - 10e5).
The dark circles represent the new knowledge you come across through reading a broad selection of books (or exposing yourself to a broad set of information). You then let it interacts with your prior knowledge (red arrow of expertise, 18c) to help you come up with new ideas and solve novel problems. See lateral thinking #todo
The transparency of the circles reflects the idea that you dive into various ideas at different levels. Sometimes you may go deep in learning a concept, other times you’ll stick to just getting a surface level understanding.
76 - Prior Knowledge is the information you have personally turned into knowledge through a lifetime of learning. It is the knowledge you use for creative problem solving with the knowledge cycle. There are two paths of acquisition for prior knowledge, represented below by A and B.
This web represents the body of knowledge out there.
The first pathway A involves specializing, working your way towards the edge of the current body of knowledge before working on expanding it (research, theorizing, etc).
The second pathway B is the process of starting from the basics in every area of knowledge and slowly expanding your knowledge base. This is essentially what a generalist would do. This is what Farnam Street calls “most useful knowledge is a broad-based multidisciplinary education of the basics”. It is the approach you take until you get to college and start to specialize.
79 - Cognitive Skills - An important part of thriving in the economy is having an understanding of cognition and the important skills that underly it. Having a solid understanding of the cognitive skills will help you improve in how you work with existing knowledge and generate new knowledge
80 - Attention Abilities - Improving your ability to pay attention helps with knowledge work because it allows you to focus for a longer period of time. Which is necessary for the deep work that is most valuable. One way to improve your attention is through memorizing a deck of cards using a memory palace technique (Newport 2016, pg 97). This comes from the study of memory champions and looking into if they have improved memory over the average person. Turns out that they do not and a large part of their success comes down to their superb attention abilities.
81 - Forming Knowledge - To work with knowledge, you first must form information in your mind . While this may seem quite obvious to you, there are good and bad ways of doing this. Improving this skill will help you learn quicker and form a more useful understanding of the world.
82 - Durable Memories - The knowledge you are forming and working with (17c) is stored in your brain as memories. You can learn more effectively by making sure information is well encoded while learning with the use of effortful processing strategies.
83 - Good Judgment - Developing good [judgment] can help you better evaluate the existing evidence, which helps in choosing the right solution in problem solving.
One way to develop better judgment is through forecasting training courses. See the work of Danny Hernandez during his time at Twitch, Open Philanthropy, and OpenAI. For more information see related interview with him.
84 - Good Reasoning - Good [reasoning] skills help you form more coherent arguments and spot flaws with existing ones. This in turn helps you form a more accurate view of the world, so you can make better decisions.
85 - Problem Solving is one of the key ways you can add value to the world. It is the process where all the other cognitive skills come to fruition and is the driving focus behind Creative Productivity Project. It is an important skill to have even if you aren’t directly solving problems and instead contributing to the knowledge base.
86 - Decision Making - You are constantly making decisions, so honing your decision making skills can help you make better use of your time and efforts in life. One example of this is deciding what knowledge is worth acquiring vs. ignoring.
87 - Communication and Production of Language - is the last step in the creative productivity project because it doesn’t matter how much knowledge you produce if you can’t effective communicate it to others. This is also necessary for gathering the resources (labor, knowledge, technology) needed to act on your new knowledge to the betterment of all. The better you can do this, the more effective you will be in the world.
88 - "Thinking is cognitive behavior in which ideas, images, mental representations, or other hypothetical elements of thought are experienced or manipulated." In this sense, thinking includes imagining, remembering, problem solving, daydreaming, free association, concept formation, and many other processes.
Thinking may be said to have two defining characteristics:
(a) It is covert—that is, it is not directly observable but must be inferred from actions or self-reports
(b) it is symbolic—that is, it seems to involve operations on mental symbols or representations, the nature of which remains obscure and controversial (see symbolic process)."