Human Skills That Outlast AI
Key Points
- Skills centered on nuanced, in‑person human interaction—such as empathy, care, and real‑time feedback—will remain valuable despite AI advancements.
- AI can generate recipes but lacks the sensory feedback loop that human chefs use, leading to less nuanced and less preferred dishes in blind taste tests.
- While AI is rapidly improving at medical diagnosis and may soon surpass doctors in accuracy, the human presence of nurses and clinicians will become crucial for delivering compassionate bedside care.
- The future job market will favor roles that emphasize human qualities (e.g., kindness, bedside manner, relationship building) that AI cannot replicate, a theme explored in the speaker’s “AI and Careers” course.
Full Transcript
# Human Skills That Outlast AI **Source:** [https://www.youtube.com/watch?v=u9nlWdWFoVw](https://www.youtube.com/watch?v=u9nlWdWFoVw) **Duration:** 00:06:52 ## Summary - Skills centered on nuanced, in‑person human interaction—such as empathy, care, and real‑time feedback—will remain valuable despite AI advancements. - AI can generate recipes but lacks the sensory feedback loop that human chefs use, leading to less nuanced and less preferred dishes in blind taste tests. - While AI is rapidly improving at medical diagnosis and may soon surpass doctors in accuracy, the human presence of nurses and clinicians will become crucial for delivering compassionate bedside care. - The future job market will favor roles that emphasize human qualities (e.g., kindness, bedside manner, relationship building) that AI cannot replicate, a theme explored in the speaker’s “AI and Careers” course. ## Sections - [00:00:00](https://www.youtube.com/watch?v=u9nlWdWFoVw&t=0s) **Human Skills That Outlast AI** - The speaker argues that interpersonal, sensory, and feedback‑driven abilities—exemplified by cooking recipes and nuanced medical diagnosis—will remain valuable because AI lacks genuine human experience and nuanced feedback loops. ## Full Transcript
if you're wondering what skills are
going to persist in a world of AI I
would challenge you to think about what
skills are most valuable for human
in-person
interaction those kinds of skills are
not going to go away and yes they can be
transferable to remote work environments
Etc but the thing to call out is there
are certain modalities of Being Human
that AI is not very good at I'll give
you an
example recipes
AI can make
recipes but pretty consistently so far
in blind taste tests humans prefer human
generated
recipes AI tends to overemphasize a
particular flavor profile AI tends to be
less
nuanced and I believe this is because AI
doesn't have an effective feedback loop
AI doesn't taste AI doesn't bake
something and say m this cookie isn't
quite right it's just a little bit dry
let me see if I can modify it humans do
and the best human chefs are going to be
repeating and getting that feedback loop
going with their own taste Buzz with the
taste buds of their customers until they
get something exactly right that doesn't
mean we're all going to become chefs in
the age of AI but I think it's a good
example I'll give you another example AI
is better and better and better at
medical
diagnosis every single model so far
released in 2024 has been incrementally
better 01 was a big jump in medical
diagnosis capabilities that doesn't mean
that we're using it for medical
diagnosis but it does mean that it is
getting better and better at answering
medical diagnosis type questions
accurately and with that in
mind I think that we are going to start
to see a shift over the next 10 15 years
toward registered nurses and nursing
type professions as being very very
valuable for humans because the human
presence matters a lot
in providing medical care but the actual
diagnosis we may be getting to a point
where the AI is actually better at
diagnosing humans with diseases than
doctors are and so again it's a
situation where you might
think that the doctor is the one that
retains the power in the scenario
because doctors have more knowledge
doctors have to go to school for more
years it's not necessarily true I think
we're getting to a point where the value
of incremental knowledge is not
necessarily is obvious because the AI
can learn so quickly could the AI do a
doctor's job today from a diagnosis
perspective not quite not really in five
years I wonder I wonder and if that's
the case then that's going to put value
back on bedside manner it's going to put
value back on humans being kind and
caring and the health care experience
things that the AI just is not going to
be able to do as effectively the robots
that come and care for you are not going
to provide the level of human care and
concern that a person can
so when I think about that I also think
about the professional world where can
we look in our professional lives for
human skills that are going to stay with
us this is part of what I'm covering in
the uh Ai and careers course that I'm
doing on
Maven if you look at your career as a
series of investments in long-term
payouts from a skill perspective I
believe that there are strong long-term
payouts still ahead for human skills and
I think the technical skills are leaning
more on AI intelligence allocation and
they're leaning more on how you think
about applying artificial intelligence
to business problems that have a human
component for instance the AI might have
thought that Google's ads describing a
child using a large language model to
write to their favorite track star in
the Olympics would be a good idea it's
topical it talks about the capabilities
of a large language model correctly and
accurately it's got a cute kid
angle but as a human it really fell flat
it fell flat because we associate the
idea of writing a letter to a star from
a kid as a uniquely human activity where
we can see the kid using the pencil to
form the letters and they're doing their
very
best and it just didn't work and
eventually Google had to pull the
ad in those situations the human
perspective on what humans like and what
humans want is going to remain
critical I'll also go into the technical
side of things I think that there will
remain a ton of value in humans
understanding and architecting large
software systems over time so if you're
in the developer
space perhaps the value of pumping out
code that is often written before and
therefore in training models is going
down but the value of solving novel
problems as an engineer in an efficient
way
is something I think that will take
longer for the AI to effectively address
and I suspect that that is because
humans have particular behavioral needs
that other humans understand at scale
and can best represent with engineering
practices so if you're trying to
understand how
cdns actually respond during a prime
time football streaming event which is
something we had to deal with at Prime
video that is going to depend on a
knowledge that people are more likely to
tune in and start streaming the game if
it is close if it is in the fourth
quarter if it is going to overtime
things like that whereas from an llm
perspective from an AI perspective even
if it's not an llm all you're going to
see is a series of previous traffic
Events maybe that's enough maybe that's
enough to design the system but I would
challenge you and I would say You're
going to to get better systems long term
with that human perspective with an
understanding of why the software is
being used the way it is so there you go
just a few little thoughts that I had on
how humans can build long-term durable
skills and areas where humans are
continuing to Excel and I think are
likely to continue to excel in the age
of
AI where we have feedback loops that are
uniquely human we are going to remain
strong contenders for highly skilled
workers professions places where we can
add value to the
market and that doesn't mean by the way
that I don't see a lot of potential for
AI of course I do it just means that we
need to learn where is AI going to be
good and where is AI going to be good by
working with us so on to the Brave New
World Together