Bearing Witness

Yesterday afternoon I spent a couple hours sitting on the stage at the high school graduation ceremony for the Academy For Software Engineering.

This evening I will spend another couple hours sitting on the stage at the high school graduation ceremony for the Bronx Academy For Software Engineering.

Both yesterday and today are busy days with lots of work obligations, board meetings, decisions, and family time.

But these four hours are the most important hours I will spend this week.

About two hundred young adults will graduate from these two NYC public high schools over this two day period.

These are young adults who made the decision four years ago to take a risk on two brand new high schools with no track record and no reputation.

But this week they are walking off the stage with a high school diploma and a set of skills in extremely high demand in today’s economy.

They also know how to talk to machines, tell them what to do, and make them work for them.

I am proud of these roughly two hundred young adults and I am pleased to bear witness to their accomplishments and the very bright futures that they all have in front of them.

#hacking education

Comments (Archived):

  1. jason wright

    The world awaits them. As they step across the threshold…that world is changing faster than at any time I can remember or have read about. So many opportunities, and yet so much confusion about how the future to come will be. Good luck to them all.

    1. fredwilson

      indeed

      1. Twain Twain

        You’re a role model and inspiration in your approach to inclusion and the heavy-lifting involved to achieve it. You’ve changed the lives of 200 young adults and they’ll go on to change the lives of 200 million users.The concern for your students is that the legacy biases in data and algos will mean “engineering” will still be associated with “male,” “white,” “middle class,” “Ivy League” so they may not be shown suitable roles by the algos or recommended by the algos to recruiters for internships etc.That’s why I HAD to organize the AI workshop to show how Stanford Glove and Google Word2Vec bias against us and our potential.Thankfully, 33 folks at LinkedIn have since watched the video in which Rachel Thomas (a math PhD, co-founder of fast.ai and co-creator of the Practical Deep Learning course) shows exactly how data biases disadvantage all of us.Hopefully, it leads to LinkedIn changing the data sets and algos of their Economic Graph and NOT using tools like Glove and Word2Vec which perpetuate biases against people and their potential.That would be a big step forward for inclusion in tech.It’s not only democratization that matters. REPRESENTATION is as vital.* https://uploads.disquscdn.c

        1. Twain Twain

          How “engineering” is associated with and fixed to identities that may not represent our modern society and our use and understanding of language.https://youtu.be/25nC0n9ERq

        2. LE

          The concern for your students is that the legacy biases in data and algos will mean “engineering” will still be associated with “male,” “white,” “middle class,” “Ivy League” so they may not be shown suitable roles by the algos or recommended by the algos to recruiters for internships etc.How exactly is this a large concern for students who have already chosen and graduated from a high school such as this? They have already decided to pursue careers in engineering and will look for suitable jobs in that area. Are you saying that hiring manager (all of them remember they only need one job) will completely ignore them because of legacy machine biases? What am I missing here?And who died and appointed Linkedin King of all recruitment activities? Not taking away from what you have possibly done with Linkedin but it’s certainly not the only way someone can or does get hired, right?

          1. Twain Twain

            The Carnegie Mellon Ad Fisher team found that when Google presumed users to be male job seekers, they were much more likely to be shown ads for high-paying executive jobs. Google showed the ads 1,852 times to the male group — but just 318 times to the female group.The bias isn’t only about gender. It’s about a bunch of socio-demographics.* https://www.washingtonpost….* https://www.technologyrevie…Personally, I’ve worked with “white, male, middle class, Ivy League” guys and it was a great experience. They trained me and promoted me and gave me the toolsets to do the things I do today.I see the issues involved being purely about whether the mathematical, scientific and economic tools we have are representative of human language, cultures and values.If those tools are no longer fit for purpose for our modern society and its future, then we have the opportunity to invent better mathematical, scientific and economic tools.

          2. LE

            Separate question I watched a minute of the video below and noted that it did some categorization of ‘hair dresser’ for women engineers vs. men. I am thinking the implication is going to be taken as ‘women should consider a women’s type career’. But do we know if it isn’t the case that the algorithm simply prioritized something that women who had searched ‘made’ them do after their initial search? That is after they selected engineering they then ended up looking at being a hairdresser (or whatever pick something)? I mean this is part of how google (or any algorithm) works, right? My point is it’s not all nefarious. Although it can be. This is no different or more nefarious than if they think I don’t have money and I search for some high priced resort and then pick a Marriott and they figure out a pattern and prioritize the next person who looks like me (in computer terms) and then does a search. Right?You know if you go to a Porsche dealer in Princeton NJ and you are a kid and you dress like shit they will still treat you like a million bucks. You know why? Because they have had the experience that there are kids at Princeton whose parents give them money to buy a nice car and as a result they will treat them as good as the most finely dressed older man. But if the same kid goes into a Mercedes dealer in a different area he will not be treated the same. Aren’t machines doing a version of the same thing with their algorithm? (This is a question, not a statement..) A form of profiling, right?

          3. Twain Twain

            Sure, it’s profiling and pattern recognition based on previous clicks and text inputs. It’s about prior stereotypes and prejudices and this applies to a form of discrimination towards the kids at Princeton as well as towards the kids in Compton.Most of those profiling and pattern recognition systems, though, may not be mathematically representative because we haven’t measured the stereotypes and prejudices with the right set of psychometrics frameworks, for example: https://uploads.disquscdn.c…* http://nymag.com/scienceofu

    2. sigmaalgebra

      A fairly general situation that might apply in some parts is: Our culture, society, and maybe even some of our genes have some old things — norms, traditions, customers, ways of doing things– and a lot of people are dependent on some of those. Then along come some new things that can make some of the old things obsolete, no longer needed, no longer effective, etc. and, thus, hurt the people who were dependent.I’m one of the ones pushing for some new things, that could be considered even radical. Indeed, once I published a research paper in mathematical statistics, and looking at the content a colleague said “Radical, provocative”. Ah, such praise! And for the old things, gee, I never fit in very well with those anyway so tend to be comfortable with change and, from the old things, don’t have much to lose anyway.Still I have to be aware, we all do, of what is happening to our culture, society, maybe even the lucky genes, our economy, our fellow citizens, others around the world, etc.I have to suspect that the strain of the new hurting the old has long been a constraint on progress and a source of pain for persons dependent on the old.E.g., last night while eating dinner, I watched a downloaded copy of the old movie Sink the Bismarck. I was struck by the high respect for that ship: Sure, in traditional terms going way back to oak sailing ships with 50 guns throwing cannon balls, the Bismarck was quite a ship. And, sure, it could be fast death to a convoy. So, the movie had the German Admiral continuing to claim that his ship was so powerful nothing on the sea could sink her.Not really so, Admiral! One of your worst threats was some flimsy little airplanes with wire, thin pieces of wood, and fabric covering the wings, when they were carrying torpedoes. Indeed, it was one torpedo hitting your rudder box that was the beginning of the end for your ship. And such a torpedo might have come from a submarine, compared with the Bismarck a tiny little thing with essentially no armor plate, etc. For more, dive bombers could have made one heck of a mess out of your superstructure and maybe penetrated deep enough to cause a fatal internal explosion.Well, soon the lesson was clear enough: The Bismarck, the Yamato by the Japanese and one more, and the US Iowa class were the last of their kind.There was another interesting, even radical, point about those ships: In a battle between two such battleships, in simple terms, the ship that landed the first, single good shot won. The guns were that powerful.As we saw in Gulf War I, there was something similar for tanks then (except for the US M1A1 tank): The first good shot killed a tank. That first shot could be from a US M1A1, a US helicopter or airplane with a Hellfire missile, or a few rounds from the gun of an A-10.Big changes. The old tanks? On the way to the same scrap yard as the old battleships.There are a lot of big changes. Some of the biggest are from Moore’s law and, then, for much more, small, solid state lasers lighting optical fibers.

  2. William Mougayar

    “…with a set of skills in extremely high demand in today’s economy” – that sums up what is a very good outcome for something that you planted the seed for.

  3. Kent Karlsen

    Great. Empower them with optimism for the future.

  4. JimHirshfield

    Accomplishment! Great to see this.

  5. gbb6

    Fred-But you’ve done so much more than bear witness, you paid attention (as Albert suggests, a scarce resource). 5 years ago you and Evan and those you brought to the table, decided the City needed to pay attention to computer science pathways, and you took up the invitation from the DOE to dive into school development at AFSE to understand the challenges on the path to CS4All. I remember the first recruitment videos and website; and the 3D plastic AFSE logos printed on a MakerBot in the back hallway of Martin Luther King, Jr HS as you spoke to the 8th grade nervous versions of the same students and parents you bore witness to yesterday. Graduations don’t happen by accident. AFSE and BASE were at least 5 years in the making, for the graduates, their families, and the network of business and civic minded folks like yourself who sustained attention for that long. The work is far from done, but builds on that solid foundation. Congrats!

  6. creative group

    FRED:This post entry requires colloquial and New York City response….Your social contributions to the community that nutured and raise the best of the best signifies and designates you as our Mother Fudger.Will not absolve you from the responsibility given. To whom much is given much is expected. Continue doing and supporting great things.

  7. creative group

    FRED:We all bear witness to your dedication.

  8. Dana Hoffer

    Are these graduates “internship ready”? I left Texas A&M with a BSME co-oping with IBM multiple times and believe in early exposure to the workplace.

    1. JLM

      .Gig ’em!VMI grads were instrumental in the founding of Aggieland and TMI.JLMwww.themusingsofthebigredca…

  9. kirklove

    Yesssssssssssss

  10. TamiMForman

    So much awesome. As a proud NYC mom, thank you!

  11. VincentWright

    One of my Top 10 favorite AVC posts of 2017…

  12. awaldstein

    You a good guy Fred, doing what matters.

  13. michaelamar

    Great title. Love this – “But these four hours are the most important hours I will spend this week.”

  14. Richard

    There is a bigger story here. It’s about time that a skills based career has “reemerged” as a noble calling. These are the tinkerers, the line workers, of the next generation.

  15. LE

    This is great and congratulations and very admirable that you made this happen.These are young adults who made the decision four years ago to take a risk on two brand new high schools with no track record and no reputation.Separately I wonder how that (new school) has impacted their college applications and acceptance.

  16. JLM

    .Good on ya, Fred. You’re a mensch.Well played.JLMwww.themusingsofthebigredca…

      1. JLM

        .Can you call a woman a “mensch”? I can’t find my Yiddish dictionary, Mrs. Pearlman.JLMwww.themusingsofthebigredca…

  17. LIAD

    Absolutely Marvellous.

  18. bfeld

    So awesome. Please tell all the young women to apply for the Women Forward in Technology scholarships – https://feld.com/archives/2

    1. Twain Twain

      My hope is that the big techco’s do more to keep women IN THE PIPELINE alongside the support of initiatives like Fred’s, yours and my ex-flatmate’s to get more female engineers into the pipeline. I was on my ex-flatmate’s case all of last year about keeping women in tech, so he created the Diversity&Inclusion program at the startup where he works. They’re Series C.* https://medium.com/tech-div…* http://www.latimes.com/busi…After the AI workshop I organized in SF last week, a male AWS engineer shared this with me: “I thought I knew all about the diversity problem but when Rachel (Thomas) showed us the data sets and how the AI works … that’s when I REALLY GOT IT.”Now he’s taking the things HE learnt (when we switched the male:female from 25:1 to 1:16) back into AWS to figure out how to code a Lambda function that might help de-bias the data too.I’ve raised these issues with the male AI PhDs I know at Intel Nervana, Uber and AirBnB so that they too work towards de-biasing the data and algorithms.De-biasing the data is an ongoing area of research in AI, e.g. Princeton University:https://arstechnica.co.uk/s

  19. ShanaC

    Happy Graduation! (and now I am thinking about how I remember that NY always graduated late)So, will NYS BoR plan on putting Comp Sci as part of the diploma requirement sometime soon?

  20. creative group

    CONTRIBUTORS:OFF TOPIC ALERT!A proud day in NYC with Fred attending the graduation and Phil Jackson getting fired as the Knicks President of Basketball Operations. Good riddance Phil Jackson!Now go get Masai Ujiri former Executive of the Year (2013) as GM. (Currently Toronto Raptors GM).https://indilens.com/wp-con

    1. JamesHRH

      THere’s no reason to celly until someone replaces Dolan as owner.You’re getting Masai when Hell freezes over.

      1. creative group

        JamesHRH:The money that Dolan provided to the slush fund of Phil Jackson Masai would accept half in a New York second. Toronto isn’t paying anyone. It is Canada for Gods sake. Wanna be New York. Stop it.The best export Canada (And we are aware of the little brother complex, eh) is their beautiful women.

  21. sigmaalgebra

    I’d want to be careful, circumspect, and have a more complete description thana set of skills in extremely high demand in today’s economy.

  22. JamesHRH

    Nice.

  23. jon williams

    Fred, so great to see you and others supporting BASE – Bronx Academy of Software Engineering. Time for mass diversity in our technology space, and these students will be part of it. My mentee student starts at CUNY CityTech, something he could hardly imagine four years ago.