Embodied Cognition by Lawrence Shapiro is a thorough and incredibly useful introduction to the emergent philosophical field called embodied cognition. Shapiro discusses three major schools of thought currently competing in the problem space of cognition. These schools are umbrellas for different hypotheses, which are competing against the standard cognitive science approach to cognition.
The standard cognitive science approach to cognition analyzes
cognition in terms of computations. In this way, the body is a kind of receiver
of information and cognition emerges from the computational processes that
happen between the body and the world. The result is a focus on these
computational processes and less concern with the interaction between the body
and its environment.
The first school of thought competing against standard
cognitive science is the conceptualization hypothesis. Instead of just
receiving information from the world, computing things and so forth, the
conceptualization hypothesis says that the unique constitution of the human
brain and body gives us certain concepts that give rise to cognition. The body
is seen as a unique interpreter of stuff through which we get cognition and
every unique type of body (e.g. species of animal) has specific cognitive
abilities in virtue of its body.
The second school of thought competing against standard
cognitive science is the replacement hypothesis which directly aims to replace
the standard cognitive science approach to cognition. The replacement theorists
think its methods and theory are better because they do not see cognition as
computational but instead as a dynamic and constant relation between body,
world and mind. In this way, the body is a dynamic system deeply intertwined
with its environment.
The third and last school of thought competing against standard cognitive science is the constitution hypothesis, which aims to show that cognition extends beyond the mind. The body is a hybrid of both its mind (internal to the body) and things outside the mind (like other parts of the body or even things outside the body). So instead of cognition as a computational model where the body receives stimuli from its environment through its body, the body is a unified whole with different components and cognition takes place within the mind but also extends beyond the brain to different component parts.
Now, these hypotheses all have their objects of study. I
won’t go into the studies themselves because it gets confusing pretty fast.
However, in the concluding remarks, Shapiro assesses the strengths and weaknesses
of each school. The hypothesis that comes out on top is the constitution
hypothesis because it can work in harmony with standard cognitive science and
contribute beneficial insights to the robust and plentiful methodologies and
tools of standard cognitive science.
This book is a great introductory book for an
academic setting or for highly motivated readers who are interested in the
philosophical ramifications of cognition. However, the bulk of the material is
not easy to get through if you have little to no experience with philosophy or
cognitive science fields.
All You Can Pay: How Companies Use Our Data to Empty Our Wallets explains how Big Data companies are not just emptying our wallets but changing our world. Authors Anna Bernasek and D.T. Mongan illustrate through easy to understand stories and thoughtful analysis how the use of data is changing the economy. From price discrimination to dynamic pricing and customization, Big Data is dismantling the traditional free market economy.
But what is the free market and why does it matter? The free
market is a market where buyers and sellers “willingly exchange goods and
services for mutual benefit.” (p.172) This supposed perfect free market is hypothetical
because nothing is actually perfect. But we rely on the free market to
establish a few conditions: (1) there’s a large number of buyers and sellers
who have power of choice to exchange goods, (2) there’s no transaction costs,
(3) there are commodity products on the market (meaning there are lots of
products to choose from), and (4) everything runs on information (and hopefully,
everyone has access to that information). But as we can guess, the Big Data companies
breakdown all of the conditions of the free market.
In a perfect world, everyone would have access to
information equally and no one would be able to take advantage of someone
because of information. But this doesn’t really exist—not even in the free
market—and the Big Data giants increasingly have all the power with access to
our data. The Big Data companies also have the power to impose transaction
costs and control other aspects of pricing. “Product customization, opaque
pricing, and complex contracts are poised to expand from their natural origins
in the world of services to all other sectors of the economy.” (p.177) And
eventually “the macroeconomic effect of the end of the free market will be a
general rise in price levels as the masters of data capture enormous profits.
To the consumer, it will be something like living in an airport.” (p.179)
Bernasek and Mongan explain all the mechanisms of control
and power that the Big Data companies hold with their data capabilities. The
problem is that there is little government oversight and little public
knowledge of this growing problem. So the first thing readers should take away
from this book is that data is a property
that belongs to the people. The authors call for readers to take more
responsibility in fighting for the property rights associated with data. “All
data is property.” (p.197) And the authors call for collective actions to take
control over our data before it’s too late.
There are two tools in particular that the authors cite to
achieve successful collective action: the law of property and the law of
contract. “Personal data, particularly intimate, extensive, panoptic data, is a
physical reality. Data is touchable and ownable. And it seems unarguable that
deeply identifying personal data, the granular portraits of our lives and
personalities made possible by big data, is owned by the individual it relates
to. That data can be sold or rented or regulated according to personal choice.
And that’s where the law of contract comes in. Individuals can contractually
control the use of their data.” (p.215)
All You Can Pay illuminates ethical concerns of data-driven
corporations, educates on the economic impact of Big Data and recommends ways
to control and alleviate the power imbalance. Read this book if you want to
learn more about the economic mechanisms behind data-driven business, the
ethical questions that result, and learn part of the history of how data giants
became what they are today.
I first moved to NYC in 2006 to attend college at the age of
18. I was very privileged in that my parents paid for everything. After
college, I set out to become an artist and the first thing I did was moved from
the Upper West Side to Flatbush, Brooklyn.
I worked as a babysitter and I paid for all of my expenses.
No more help from mom and dad. I had a one-bedroom apartment that I shared with
a friend who lived in the living room. I also rented a studio space to paint
in. I didn’t make enough money to survive so I had to rely on other (sporadic) forms
of income and being extremely cheap.
My exit strategy was to go to graduate school. I spent the
entire summer and fall preparing my applications to graduate schools. In the
winter and spring of 2012, I was struggling financially and looking forward to
moving out of Brooklyn. After getting accepted into graduate school, I finally
left Brooklyn in July of 2012. I lived in Brooklyn for just over a year.
So here is the data… I recorded every single penny that I spent while I lived in Brooklyn from October 2011 – July 12, although the time I actually lived there was May ’11 – July ‘12. This data focuses only on expenses, not earnings, because I earned some of this money through very shady means, which I am not proud of, because one of my jobs was suddenly cut because of layoffs. Nevertheless, the good things that came out of this period are that I learned how to manage my own finances on a very tight budget and I learned the NYC hustle. Rent was my biggest expense at $500 a month. I shared a one-bedroom apartment with a friend. It cost $1000 total in Sunset Park, Brooklyn in 2011. I lived in the bedroom and my friend lived in the living room. We split the rent evenly because my friend was generous. But it was not the most comfortable living arrangement. The second biggest expense was food, including cost of groceries, restaurants/eating out, and snacks/food on the go. This accounted for between 10-30% of my monthly expenses. Next, a monthly unlimited metro ticket was $104 and sometimes I had to spend more if I lost it. Finally, I spent a good amount of my income on both my art studio and art supplies, sometimes up to 16% of my monthly expenses but not any more than that.
Over the course of 10 months, the two biggest anomalies occurred during Christmas holidays and during my move out of Brooklyn in July. In December, I spent extra money on a plane ticket home, gifts and mailing gifts. Similarly, in July, I spent money on an airplane ticket, mailing all of my belongings (about 30 boxes) via USPS to my new home, and hotel costs.
Overall, I was able to consistently keep my monthly expenses
below $1800. But there was an upward trend to spend more as I lived in Brooklyn
longer excluding the month of July when I moved. This was accounted for by a
change in my living situation. I got a new roommate and I elected to pay more
for rent because I lived in the private bedroom. Perhaps I also got better at
tracking my expenses too.
Granted, if I stayed in Brooklyn, I could have found a
better job to live more securely and earn more income. But this was in 2012.
Cost of living has sky rocketed since then. For a single artist with no debt,
living so cheaply in NYC is possible but, let’s be honest, living in purely
survival mode is no way to live.
It was beautiful to live in an artistic epicenter like Brooklyn. I learned a lot about myself and about making a living. But I would not choose to live there again because of the financial struggles. First, the cost of living is exorbitantly high. Second, the quality of life is poor—read: smelly, loud, dangerous and stressful. Third, I was far from my family. Fourth, I didn’t have reliable income. Fifth, the weather sucked. Again, I love Brooklyn but I would never live here again – not even if I were making boat loads of money. Why? Because I can live on a similar budget very comfortably in many different places. The costs of living in NYC are just too many.
In a scholarship application for a coding boot camp, I
was asked the following question and it really bugged me for a few reasons:
In a traditionally male dominated field, what benefits do you think women can bring to the class environment and technology field? What makes you the most deserving candidate for the scholarship?
Here was my
There are two
answers to this question that address what is asked. The first answer accepts the
premise there’s something inherently different between men and women. And
traditionally, most people accept this premise and a response might list the
inherently different and beneficial qualities of “women” to include, for
example, diverse group dynamics and work styles, solid managerial qualities,
strong empathetic perspectives and etc.
second type of answer would not accept the premise that there is something
inherently different between men and women and would even go so far as to
argue, in a radical feminist fashion, that the qualities of “women” and “men”
are not consistent with gender but instead social constructs that
societal/cultural norms instill in artificial types (‘men’ and ‘women’).
side on the radical feminist perspective to answer this almost misogynistic
question about what benefits women might bring to the table (if only they had
shot). Women bring benefits to their work or class environment as much as any other
person no matter their gender. But not categorically women qua women.
isn’t a bad one for a scholarship application, but it is discouraging to ask
what women can contribute to the technology field. What about other gendered
folx? What have women already contributed to the field? And what can men or
persons in positions of power and privilege do to enable minorities to impact
the field? These are the real questions that should be asked.
So herein lies the answer to the deeper question:
people learning/working in the technology field or any field should acknowledge
the disparities of race, gender and sexual orientation on larger scales. And people
in power should exercise their influence and authority to institutionally empower
women, minorities and other gendered folx within the field and change that
field and society in turn. The field can benefit itself by stripping away
barriers and assumptions that have been taught through generational
stereotypes/norms. This work needs to happen institutionally.
believe men and women are inherently different. I think society constructs
limitations and barriers and institutions and businesses can fight and correct
them. Being a gay, biracial cis-woman who just entered the technology field, I
want to work with people that respect and acknowledge the need for equality and
dignity for all. And I’d like to exist in any place as myself and not a gender.
Bootcamps or career
accelerator programs are short term education programs designed to help you learn
new skills and find a job. If you are thinking about attending one, I will share
some tips about finding a bootcamp, my story about how I chose to attend Codeup
in San Antonio, TX and how I got funding to attend.
My first tip is to spend
at least a few months to a year researching the topic you want to study and the
bootcamps available. There are tons of resources online to learn programming. I
will provide a detailed table below of the courses I took, most of which are
free. While you are learning the basics, start to learn about the bootcamps
that teach this subject, read through bootcamp curriculum, take notes on
tuition costs and start dates and note whether or not they provide scholarships.
This first step is crucial for figuring out if this topic is something you are genuinely
Secondly, when you start
researching bootcamps, you will find that cost of tuition can be high. The best
strategy is to look simultaneously look for funding and bootcamps. First look
locally and seek out local and federal grants to attend based on being
under-employed, unemployed or under-represented in the field (minorities). I
was only able to find funding because I met with a local career training
program which enabled me to access local and Department of Labor funds. If you
don’t meet the criteria of being being under-employed, unemployed or
under-represented in the field, then don’t worry! There are still other
scholarships and loans out there.
Warning!—only start to contact/call
up the bootcamps when you are comfortable with your basic skills in programming
(or whatever you are trying to learn) and when you are committed to attending.
Bootcamp admissions will aggressively seek you out. They want you to attend
their courses. You should have clear intentions about what you want to do, how
much money you want to spend, and how good you are at programming. Just be
honest with the people you speak to about your circumstances. This is a process
so take your time. Often, if you get rejected from a bootcamp, you can still
Lastly, there are almost
always loan companies that specialize in loan for students of bootcamps. If the
cost of tuition is still prohibitive, you can consider loans as your last
option. In most cases, these loans can be repaid easily with the job you will
(hopefully, most likely) get after you graduate. Some bootcamps offer refunds
if you don’t get a job (with conditions) and others offer deferred tuition
where you don’t pay anything until you get your first job.
As for my experience, I learned about Data Science online and spent 10 months researching the subject and bootcamps. I took a slew of courses online to learn the basics, which I will share below. Then I started to apply to bootcamps. Ultimately, I was able to find Codeup in my hometown. I visited their campus and spoke with their admissions representative about funding. I loved that this school was in my hometown, so it was a practical choice for a full-time program. I also liked the instructors and admissions people that I met. The admissions person told me about their funding options and sent me to a local career training program, which informed me about local and federal grants that were not easily accessible online. Working with this local program was long and uncertain but I stuck with it. The real reasons I was able to get funding through them were because I had been under-employed for years, I had used up all my savings, I was living at home with family and I was unemployed at the time that I applied for the funding. In the end, I chose Codeup because I was able to find funding, it was in my hometown and I genuinely liked the people I met there, especially Maggie Giust, the Senior Data Scientist.
I will share a table of
the exact funding amounts that I got below. This will probably not be the norm.
I got extremely lucky with my funding.
All in all, this whole
process is precarious, scary and hard. You should give yourself plenty of time
to research and learn about the process, the bootcamps and the subject you are
trying to study.
If you need any advice,
please feel free to contact me directly. And if this was helpful please send it
along to anyone you think would benefit from it.
Join for free. Audit courses for free. Some times you can get stuck when they ask you to pay in order to submit quizzes. If this happens to you, just skip the quizzes or sign up for a “free trial” and cancel before you are charged.
Easy, work through exercises slowly. Spent about 1 week on it.
Update: As of October 2019, I have learned that Project Quest no longer has funds from the Department of Labor, which was the majority of my funding. Please contact Project Quest directly for more information about the resources that they currently provide.