Tricia Wang (designing for perspectives: the secret for
learners to thrive in the 21st Century)
The individuals are getting too much of the blame. We need
to design for perspectives, (@triciawang ).
Sally Ride was the first female astronaut. Once she stopped
flying she developed earthKAM, which enables teachers to use the camera on the
space station. The students can select the coordinates, and it gives the
students a hands-on space experience.
The power of using tech and learning, at best the students
really feel science. It introduces a new perspective for students. Video and
photography provides participatory options for learning. Technology has seen so
many innovations now applied to learning, it is mindblowing. Machine learning
is a fancy term to describe what we do with computers, where computers get
actions from humans.
Machine learning is a 3;7 billion industry, but what are its
limitations? Machine learning still requires human designers and quality data.
If the humans overseeing the training are not aware of their own biases, these
biases result in the output.
Technology has not increased our understanding of the world.
Example: the white interpretation of google photo’s. It is a result of failing
to see outside of our perspective.
These technology mishaps happen a lot. Machine biases, Propublica
23 May 2016. (the high risk offender example).
Machines are directing our learning, as such biases in these
machines might result in more biases in learning. No one wants these biases to
be embedded in machine learning. But the outcomes reveal the limited
perspectives of their creators. And this happens easily, perspective collisions
happen.
Representing heterogeneity is a difficult challenge. We are
still not truly globally connected. The social part is something all of us have
a hard time with. Getting a multiplicity perspective is the challenge. There s
a lot of confusion, as everyone gets to speak, this means all of that ends up
into the social texture of life. So we need to teach people to navigate their
own lives through this new social, machine lead system. Perspective shifting, a
new form of media literacy, taking into account people that are not like you.
This will be one of the most critical skills, but humans need to be trained for
this. It is a learning behaviour, so qualitatively learning these skills is
possible and should be a priority to enable a global world with true equality.
Relying only on quantitative data, it risks us to be blind
by the known. This is why we need people that can actually address these
multiple perspectives. To get outside the binary: replace the binary divide
with the connected network, to ask different questions (computers replace
humans), but why do we not ask what humans can do to work with computers to
reduce biases. Always integrate both quantitative AND qualitative data to
eliminate the risk of bias. In a pluralistic society, we need this approach.
Look up caroline synders or sinnders… for work with machine
learning and ethonographers.
Andreas Schleiger (supporting learners globally to own
learning)
The last couple of years we all got experienced at coping
with economic crisis. If you look at who found solutions, skills seem to be the
key driver to battle inequality or crisis. People at the high end of the skill
spectrum see themselves as actors, while the low end sees themselves as
objects.
Even today, corporates tell us there are no skilled workers,
yet more people are looking for jobs.
So it is about skills and using them, learning them.
How to be ready for social problems, like jobs that will be
erased. It is not about robots, just about automation. But augmented reality
can bring the real world into any location. Google knows everything, and there
is a huge challenge that is coming our way. There is no longer a digital
economy. The economy is a digital economy.
People work harder now, then ever before, but the declining
levels of productivity is affecting work. There is a growing divide that people
with the right skills have less opportunities, thus those without skills have
even less options.
The race between technology and skills.
Digital problem solving skills: finding solutions for every
day problems. Only 1 in 5 people above 50 years can do this. Even if we look at
people 16 – 24 suffer, as only one in two young people can solve every day
challenges.
Lots of people are being left outside. The only area where employment
grows is the high skills jobs. This is where the economy is quite stable
(admittedly, the pay is decreasing for these jobs).
What skills are important: knowledge, integration of
different fields of knowledge (think like historian, philosopher, technology…
all at the same time will increase your skills and stability). And then looking
at details to solve problems via different viewpoints.
The world rewards for the opposite, for thinking about
systems, not the details.
Digital literacy, global literacy… those different
perspectives become the challenge.
Skills that matter today is critical thinking, creative
thinking. Solving complex problems, social skills, communication…
But something controversial as skills is: resilience,
figuring out problems when you cannot see the solutions, curiosity,
mindfulness, ethics, courage, leadership, inclusion, empathy. Making judgments
becomes more important, that is complex. Self-awareness.
Everything we do reinforces what we did when we were young.
If we think of the science changes… it is amazing, we have developed 3D
printing, iphones, google maps… you no longer need to teach people something,
but skills.
Fundamental success in life: numerical skills (eg data), there
is a direct relationship between low skills and declining jobs.
You no longer need to accumulate degrees, but contemporary
skills mentioned above.
Literacy skills, learning to learn, cross-sectional skills. We
need to teach people these skills to enable them to be able to find the right
jobs.
Roger Schank (who owns learning, not you, maybe AI can help).
This is a person you just need to talk to. The talk will be hilariously invigorating.
Who owns learning is my question. Everyone but yourself. As the system tells you what to learn, with similar requirements, interpretations of what is best.
Eliminate testing. The politicians support the testing industry. And forcing testing, forces what teachers need to teach.
Let’s built online learning that does not suck and really teaches us a lot of useful skills.
Artificial Intelligence: at a certain moment it was put in the freezer due to over-expectation at some point. But now it is again a big business.
At present models human intelligence, but it is not. Schank mentions AI mentor (look up).
