2020 Times Are Changing — Overview

This OLLI class tracks changes in society due to the Corona virus and ongoing events during the summer of 2020.
We will post links to news and opinions worth discussing during our weekly hour of Zoom. Let’s use our lifelong learning backgrounds and methods to make sense of the changes we’re witnessing.

Here’s a model:

  • Ongoing changes measured economically or otherwise.
  • Practices and institutions that are, for sure,fading away.
  • Opportunities that open up, to be defined.
  • Known unknowns, unknown known’s, etcetera following from these changes.

Proposed Topics:

    education and Educational Institutions
  • Technology.
  • environment and climate change.
  • Public Health, the pandemic, quarantine, medical services, and disablism.
  • Travel, recreation, life style, housing, and finances.

class members are invited to post links to article, podcasts, videos, and other resources that clarifies these changes. Come on, news nerds, share your reading with a link and a comment for discussion.

This web site has pages for the topic resources. Click the topic page and look for an open box. Insert a name than type into the comment box. You might need to scroll and might want to write then copy and paste. Your comment might not appear immediately as the facilitator will moderate at least twice a day.

Anybody want to write an article? Keep the text simple and we can add another post.

What’s the stuff in the menu at the top of the web site? These leftover topics from a 2012 class around presidential candidate opinions has some well written problem statements as well as political justifications. Comment there, too.
Finally, remember is just another free web site, this one loaded with Susan’s past course materials you’re welcome to read. Thanks to WordPress for enabling web publication experimentation. The authors of links we post may trace back and gain appreciation of how their material has been used. That’s the World Wide Web in action.

Original Course Description:

2020 Times Are Changing!

This class is for news nerds who want to organize their information and viewpoints about the 2020 changes in our lives. We’ll examine critical systems such as: Public Health; Educational Institutions; environment and Climate; Technology and Media; and Travel. Each topic has persisting trends, dramatic changes, slow evolution, and enough unknowns to challenge any OLLI member’s wisdom and experience. The facilitator will maintain a web site for links from experts, news, and personal opinions. Controversies and misinformation are welcome. Example subtopics might include: Bill Gates vaccine laboratories; the future of local colleges; effects of Zoom; your next adventure trip; road traffic patterns; future OLLI courses. how will our worlds change in the next five years? Research, conjecture, and discuss for 6 hour-long meetings backed up by a growing online webliography. Roll with the changes!


Week 6 Environment and Climate Change

Questions for Discussion:

0. (Forgot last week) How has travel changed? Business travel? Recreational travel? Educational travel?

1. How has the pandemic changed the long, long mission of controlling climate change?

2. What are similarities and differences between pandemic models and climate change models?

3. What have we learned about government and social capabilities for managing epidemics and climate change?
4. Are there new opportunities for managing climate change due to the epidemic? Did some problems go away?


Ongoing OLLI: water management; electrical/nuclear/wind/solar systems; seminar climate change; classes on North and South Poles; Great Decisions; climate-based fiction; others?

From Deb
Tech Review Newsletter and magazine

From: Weekend Reads from MIT Technology Review
Date: Sat, Jul 18, 2020 at 6:07 AM
Subject: Amazon creates $2 billion climate fund to cut emissions>

We delve into carbon capture and carbon sequestration—sucking carbon
dioxide out of the sky or catching and storing it before it leaves power

From Cindy
Climate change progress report

Brookings Institute reports and podcasts

What coronavirus teaches us about addressing climate change


Philosophical piece on history by science fiction writer Kim Stanley Robinson

Books on Climate Change

Ed recommends “The Uninhabitable Earth”
David Wallace-Welles
See TED talk

Susan likes 2020 plant scientist’s guide to experiencing climate change, by Hope Jahran, author of memoir “Lab Girl”
(My New Book!) The Story Of More


Informative podcast, “America Adapts”, interviewing Michael Mann “dire predictions” and climate scientists and how, right now, urban planners are adapting to rising seas, droughts, etc. as a new professional speciality


Turning from non-fiction, “climate Fiction” is science fiction based in climate events and changes. Short story collections include “Loosed Upon The World” by John Joseph Adams and “Everything Changed” 2 volumes free from writing contests at Arizona State

Reviews of climate change, nonfiction and fiction


Week 5 Economics of 2020 Changes

Let’s discuss changes, opportunities, and losses in terms of the physical and economic world we’re used to locally. Examples:

How will the work force change? Lost jobs? New jobs?

How will travel change? local? national? international?

Will the age demographics change? graduates leaving? retirees staying?

Are new companies moving in? Is the “work at home” model good for local jobs?

How does the epidemic affect local medical services going forward? Are disability trainers available?

How will state and federal fund changes affect schools? roads? safety services?

Is there a post-pandemic recovery plan? next time?

How will college education changes affect the local economy?

What other events, e.g. the 2014 Northern Arizona Outage, over-take the local economy? How will climate change affect economy and safety?

What is the local pandemic response model? individual choice? facility lockdown? national advice du jour?

Will the 92% white majority continue, and maintain the economy? Is this a strength or weakness?

What aspects of community culture are going, going,…gone? What changes open new opportunities?

What are our best local and regional news sources tracking the 2020 changes?


What would you advise a 30-year-old to adjust to 2020 changes? careers? finances? health? location? family? education?



Week 4: Internet Technology Past, Present, Future

Internet technology: Past, Present, Future

Resource — Internet Pioneer Vint Cerf

  1. How a virus survivor views a fragile society, changes facing social media, handling misinformation, Internet safety, education inequality, space Internet and Internet of things … from Radio Corona

  2. Tales of Internet past, present, future…
    “Last/next 40”

  3. Social movements

    People-centered Internet

2020 Internet Changes: questions for discussion July 9

  1. Who runs the Internet? Opportunities? Lost Capabilities? Worst thing that could happen?

    <LIIs the World Wide Web same as Internet? Could there be another WWW?

  2. IoT refers to things, e.g. household, with Internet connections. Will such things change virus models? increase/degrade during pandemic downtime? identify pandemics?

  3. Will “equal access” change after 2020? How will schools work?

  4. Is handling of mis-information changing during 2020? Does “life or death” information matter?

  5. How has the Internet changed job markets during the pandemic? the overall economy?

  6. Opportunities: deathbed family reunions; better remote education? controlled information quality?…

  7. Disappearing technologies and practices???

Summary of Discussion TBD

Add links below to related Internet resources and technology in general.


Understanding the epidemic

Week 3 Main Questions

0. What are best sources for News Nerds on pandemic issues? Who are wisest writers?

1. Using the terms “reproduction rate”, “flatten the curve”, “distancing”, etc. let’s succinctly describe our epidemic situation on July 2, 2020.

2. What changes have worked to better our situation? Is “contract tracking” in place and working? what are privacy issues?

3. What actions propelled the rates? what’s the prognosis for November 2020, epidemic-wise?

4. Next topic 1: how do the 2020 changes affect society – jobs, travel, medical services, policing, …?

Another topic 2: Pundit Internet pioneer survived the Corona virus and is speaking about Internet successes and needs for change. He’s google-biases ed, of course. Who’s the wise spokesperson on social media and changes coming there?

Big topic: how have 2020 changes affected climate change? what have we learned about ricks and prevention?

On to epidemic-related models….

  1. Cindy points out “all models are wrong, some are useful” so what makes a model useful? dangerously wrong? working with available data?

  2. … a side trip into normal science going on during unusual times. When parts of the world shut down, nature offers new habitats for experiments: ocean noise, atmospheric pollution, and the psychology of boredom …. a fun listen

    The Natural Experiment

  3. —–

    How do viruses “spill over” from animals to humans?

    The article suggests “ask a computer”, presumably endowed with “artificial intelligence”. A cynical definition of AI is “a buggy algorithm with interesting results”, and for the Machine Learning brand of AI “biased data in, biased advice out”. That is, computation, data analysis, guesswork (heuristics), and spinning the wheels of algorithms can lead to suspicions about the real world that may, or not, lead to beneficial decision-making. This article seems fair and wise.

    Bats are frequently implicated for viruses, making me think of the touted world’s largest urban bat colony in Austin.

  4. More on the “issue Are college sports goners”? probably should read “Gone for N years are many non-revenue campus sports while football and spirit-raising sports survive.”

    The business model for sports in academia will change as long as contact/distance limit performance and crowd participation. Which aspects of academic operations will suffer from lost revenue? Which campus amenities will change as students choose colleges for remote/onsite education? Administrators must decide among disciplines, support activities, facilities, and already changing professional schools with a population excluding foreign students.

    Ed’s recommended readings are
    “college sports in cricis”

    and how sports interact with leadership through special programs, similar to ROTC? ). Are there opportunities for 2020 changes to motivate and implement programs that improve the organizational capabilities, moral spirits, and strategic thinking for disciplines through sports? ditto theater, art, music, …

    So, what are better wordings for “opportunities” and “goners” in a poll to clarify this hot issue.

Welcome to the exponential world of curves, caveats, and life under the rules of epidemics. It’s complicated!!!

  1. A few readings that build vocabulary and intuition, not for the faint-hearted….


    General discussions of changes post-pandemic

    … Thanks to Dirk’s for AARP article

    Thoughtful writers summarize

    Articles like these offer a better basis than education for a poll.

  2. —-

    A Moment of News Nerdity: What are your preferred resources for understanding the pandemic: traditional news, e.g. NYTimes, WaPo; academic sites, CDC, e.g. Johns Hopkins; active opinion, e.g. TED talks, YouTube; podcasts, e.g. The Daily, Slate Politics; health advisories, e.g. AARP, Medicare; local updates, e.g. DCourier, AZ central; social media, Twitter, Facebook; ..; explainers, e.g. Wikipedia, Apple News; .

    What resources do you consider worthless, dangerous, fake, satirical?

    Is Wikipedia useful and accurate and up-date resource?


  3. Epidemic Model Lingo:

    reproduction rate (RR), herd immunity, immunity, contact tracing, compartments,
    and the ever popular
    “Flatten the curve”. What data is curving? What social actions purport to flatten? How?

    Does international data show successful flattening? Is it too early to know if there is “life after this pandemic”?

    How reliable are estimation models? Debra sends an example of difficulty reasoning around uncertain immunity

    Where did the 6 feet distancing model arise?

    “contact tracing” ramps up social processes for health organizations dealing with previous viruses and immunization. Blue tooth phone apps could supply distancing and contact data if Apple and Android interacted. A specialized portable token with no normal interface (like a coin) could increase contact tracing. Oh, the privacy issues…

    Seems to be working in the Bay area


  4. An epidemiological “lab” and tutorials

    Overall, Wikipedia has simplest explanations IMHO and it’s referees are tough.

    Classical discrete math problem: each infected individual generates 2 infections per day from an un-infected population of millions. Starting with 1individual, how many days does it take to infect 10,000? 100,000?


2020 Changing — Education

Add resources about education and educational institutions as they will change during ad after 2020.

Resources related to education

Changes in Education

Changes We Observe

  1. Elementary school students learning differently due to online after closing
  2. College applications switching due to online/campus choices

Educational Processes Likely to Disappear

  1. Grade school teachers provide emotional stability (versus frazzled parents)
  2. College entry exam frenzy, more pragmatic choices

Opportunities Arising From Changes

  1. Streamline curricula, solve problems versus theory of solutions
  2. Universal basic service for 18-20 year olds to learn skills and organization and service in diverse surroundings

Questions: “Known Unknown”? “Unknown Known”?

  1. College Survival rate, departments retained, faculty/administration job descriptions
  2. The role of sports in education – facilities, crowds, socialization

OLLI Singularity

A Play: “Wearables, Take a Hike”

Wearables, Take a Hike!

by Susan L. Gerhart, March 1 2018 for Spring 1 YC OLLI Class on “The Art of the 10-minute Play”, facilitated by Alex Gabaldon

Synopsis: A group of hikers try out networked, wearable devices to enhance their outdoors experience. Things go wrong.


  • Protagonist Jack: – hike leader; dull, well-intentioned techie,
  • Jill (co-leader): knows her tech, problem-solver.
  • Bob: data-driven, infatuated with his Quantified Self
  • Carol: – friendly, routine hiker, has puppy at networked home.
  • Ted: — goof-off, awkward, bird-watcher.
  • Alice: nervous hiker.
  • Max: – Easily gets off track, also has smart home.
  • Sue: – quiet, calm lawyer. ,


—- Man and woman greet each other at picnic table below Big Toe Butte. —–

Jack: : Good morning, Jill. It looks like your ankle healed nicely after your tumble at last year’s hike up this hill.

Jill: : Yes, and I can hardly see the scar on your head from your Fall, Jack. Remember what the physician assistant told us. We were both dehydrated when we came into Urgent Care after our accidents. She said we should take short drinks every 10 minutes when we’re climbing and a big gulp of water at the top of the hill.

Jack: She was right, Jill, we needed better technology on that hike. This year I got us those new wearable, networked gadgets.

Jill: I’ll yell every ten minutes “ALL SWIG!”. Have you planned our bathroom breaks?

Jack: : Yes, there’s an app for that!

Main Scene: Big Toe Butte

—- Picnic table at base of Big Toe Butte in background. Bob, Carol, Ted, Alice, Sue, and Max arrive. —–

Jack: Welcome, fellow ILLO members. Today we’ll hike this magnificent mountain using these wonderful devices Jill is passing around. They are called Gurgle Glasses.

—- Jill hands out ugly glass frames attached to ear muffs to each hiker. —–

Jack: First, we’ll hear from Doctor Bob about how Body sensors can tell us the optimum number of bathroom breaks on the hike.

Bob: The Quantified Self movement says we can completely understand our bodies by collecting data. I gave you a bracelet and app to track yourselves all week. Please yell out the number the app shows.

—- Shouts of 9, 3, undefined, 20000, . —–

Jack: Thanks, Doctor Bob. It looks like will get valuable feedback on the accuracy of its prototype. And, you’ll get a commission, right, chuckle,

All Shout: So, how often do we stop to pee

Jack: You agreed to swig water every 10 minutes. We’ll be at the top in 30 minutes. Good luck.

—- Groans and rush to nearest rest room Hikers reassemble. —–

Jack: Now let’s get acquainted. Your Gurgle Glasses will read you the biography of another hiker to chum with along the trail.

—- Hikers put on glasses and ear pieces. A fight breaks out between two hikers shouting cheers for bitter rival Ohio Buckeyes and Michigan Wolverines. —–

Jack: See, we already have a pair of new friends.

—- The hikers start moving up and down and around simulating a trail. —–

Carol: OMG, I forgot to fill puppy Snuffy’s water bowl before I left home.

Jill: Smart Home to the rescue, Carol!! Just text the right spigot to refill his bowl.

—- Carol frantically flicks around her screen. —–

Carol: The sun is too bright. I can’t find that spigot on the house map.

Jill: It’s too bad you’re using those half-vast Gurgle Sprinkles devices. My Snapple works with Voice so I don’t need to see the screen

—- Carol pokes furiously at her screen turning on all spigots. —–

Carol: Oh, Snuffy, I’ll be home soon.

—- Puppy barks sound from device. —–

Jill: Snuffy will be fine, but he probably made messes. The noises scared him after you turned on all the water devices at once.

Jack: Wonderful, there’s an important lesson. Set your Smart Home to remind you to fill the water bowl before leaving.

—- Jill stomps and jiggles her feet. —–

Jack: Jill, why are you dancing every time you stop walking?

Jill: It’s those Blister Prevention boots I bought after last year’s hiking accident. I can’t adjust the lining liquid. That fluid attracts fire ants. !

Jack: Please don’t remind me about last year’s fiasco.


—- Yell of pain and struggle. —–

Jack: That’s Ted. His QuantifiedMe bracelet is stuck in a cactus.

Jill: Here’s the emergency kit. Oh, no, it’s full of Girl scout cookies!

—- Swearing and cries of pain. —–

Jack: Ok, Ted is free from the cactus. He will heal quickly. Next hike, let’s make sure we bring the First Aid box. Don’t forget instructions. I’ll take a cookie.

Ted: I saved my bird identification sound app. Does anybody recognize a Peregrine Falcon?

Alice: Oh, no, there’s a rattlesnake at 10 o’clock on my left side! Help!

Jack: Alice, are you using the Snake detector app in Gurgle glasses? It’s buggy! Some sounds set off a false alarm. Ted, please turn off your bird call app.

Jack: Don’t you think this year’s hike is going much better than last year? Look at all the gadget data we’re getting!


Jack: Where’s Max? Gurgle Spy reminded me that he often wanders off track.

—- Maxis somewhere off trail. —–

Max: That’s awful! Some geo-cachers have stomped this beautiful wild mushroom patch.

Jack: Max, we need you here.

—- Max returns with brown bulbs (a deadly mushroom). —–

Max: Look at these ‘Amanitas’! I’ll make a nice Asian omelet when I get home.

—- Max pulls out his glasses and starts speaking into them. —–

Max: Siri,or Alex, or whoever’s in there, beam me home to my Wired Casa network!

Synthetic Voice: Good morning Max, this is MyFriggingApp. How can I help you?

Max: How many eggs are in my refrigerator?

MyFriggingApp: You have two left. Would you like to upgrade your Amazon drone to deliver a dozen eggs before noon?

Max: Yes.

—- Buzzing noise then. —–

MyFriggingApp: Max, Gurgle Health noticed that you had a 3-day bout of diarrhea after this hike a year ago. I’m sending a mushroom identification chart to Jack and Jill.

Max: no, wait!

—- Everyone’s device goes off loudly, then crashes. Hikers reboot. —–

MyFriggingApp: Sorry Max, your Wire Casa has reported this feature Interaction error to Gurgle-Cares. Please repeat what you wanted.

—- Max stuffs the device into his backpack and curses the heavens. —–

Jack: That feature would have been really cool, if it worked. We’re almost to the top. I see Big Toe from here.

Jill: I’m looking forward to a nice cool drink from the well, just like the Urgent Care doctor ordered. Then, I’ll splatter myself to cool down.

Top of Hill

—- Hikers all reach the top, circling a package swinging off a tree branch. —–

Jack: Oh, no, somebody moved the well faucet. Some geo-cachers left a logic puzzle telling us the new location.

—- Jill unwraps the paper and starts to read the puzzle. Sue is sitting quietly with Indian flute songs wafting from her earpiece. —–

Jill: Anybody know how to solve these puzzles?

Sue: I can! We practiced these puzzles to take the Law School Aptitude Test. That was long ago before The Great Trickster jailed lawyers.

—- Sue, pulls out a keyboard, types, while other hikers stand around. —–

Sue: Voila! This says the well faucet is at
N 34° 32.175′ W 112° 34.955′ — Didn’t we pass that on the way here?

Jack: I declare this trip a great success! we made it to the top safely. We learned so much! And there was scenery, too!

—- Hikers clap tepidly. Their devices all rattle with some message. —–

Jill: I’ve just sent you the ILLO evaluation form. Please fill it out while we’re resting.

End of Hike

—- Hikers tromping down to the bottom, back at the picnic table. Hikers head for rest rooms, leaving Jack and Jill. —–

Jack: Wasn’t that cool? We tested many devices on real humans in tough terrain. ? I think everyone liked this hike.

Jill: Several evaluations ask for Sue to teach us how to solve those logic puzzles. One person suggested you lead a nursery rhyme class.

—- Jack walks over to his Segway. —–

Jack: Look what I have here, the latest Segway model with autonomous steering. It recognizes all kinds of object in the street. I can even nap on the handles while I cruise home safely. Bye, See you next year!

—- Jack waves as he wobbles off down the roadway while Jill watches. Soon comes a blood curdling animal snarl and a human scream. —–

Jill: Oops, that Segway street object recognizer wasn’t trained for mountain lions.

—- She pulls off and stomps on her Gurgle glasses, then pulls out a flip phone. —–

Jill: Hello, 911 we have a big problem at Big Toe Butte.



Internet History ala California

For Carol Hammond’s “California Here We Come” class, Fall 2, 2019, OLLI at Yavapai College Prescott AZ

Familiarization Questions

  1. When did you become *Internet*-enabled? (newbie) after 2000 or (old-timer) 1980-1999 or (confused) before 1980???
  2. Who are the trusted wise “fathers of the Internet”? Where are the “mothers”?
  3. How was Internet history influenced by WW II? Sputnik? Vietnam?
  4. Where in California was the Internet incubated and nurtured? Was there an East-West migration of people and corporations?
  5. Were there search engines before Google? How did libraries search collections?
  6. Did “Zuck” (Zuckerberg) Invent “social media”? If not, who did?
  7. Where is the Internet Archive? Who runs it?
  8. What is “surveillance capitalism”? Is it good? or evil? What comes next?

A Time Line

From War To Imagination

  • World War II transition to peacetime work vision of MEMEX “As We May Think” by Vannevar BushJuly 1945 consider a future device in which an individual stores all his books, records, and communications, and which is mechanized so that it may be consulted with exceeding speed and flexibility. it is an enlarged intimate supplement to his memory.
  • Sputnik 1957 led to government science invested NSF and ARPA (Advanced Research Projects Agency), also Eisenhower-era science education funding.
  • 1960s- Research organizations: Rand (Santa Monica), Lawrence Livermore and Berkeley built California scientific workforce.
  • Network idea “packet switching” grew from RAND and Britain National Laboratory and UK communication industry
  • UCLA researchers (Klein rock and Estrin)and Van Nuys high school friends (Cerf, Postel, Crocker) had a network lab funded by ARPA.
  • East Coast industry funded a network of time-shared computers and routers (called IMP) to make packet switching work.
  • Story: 1969 First network message, “LO” , to log onto other ArpaNet computers, UCLA to Stanford Research Institute, then Santa Barbara and Utah. ,

Networks Multiply

  • 1970s USC ISI (Information Sciences Institute), 4676 Admiralty Way, Marina del Rey, Network Working Group (under Jon Postel) developed mail protocols, domain name system, ‘request for comment’ process
  • Xerox Corporation form PARC (Palo Alto Research Center) “Office of Future”
  • early 1970s applications: Project Gutenberg at U. Illinois also PLATO educational system, graphics at Utah, hardware at Washington U, AI at MIT
  • * 1980 joint project (Postel, protocols), (S Gerhart, specification and verification) *email sgerhart@ISI-A
  • 1980 Internet protocols, Vint Cerf and Bob Kahn, fostered multiple networks MilNet, NSFNets, and regional networks
  • 1998 Death of Jon Postel, loss of process and wisdom and trust <*Video: a href=””>About Jon Postel and the ARPANet at Internet Hall of Fame (YouTube)

Social Computing Grew

  • 1980s “The Well” virtual community, ‘whole earth’, Sausalito
  • Usenet public discussion (Tom Truscott),subscription groups on technical and social topics . Observed Godwin’s Law (“eventually discussions end in Nazis”)
  • Hypertext theory structured information, then was ignored by WWW

Organizations Inter-connected

  • 1989 Swiss CERN lab, World Wide Web, (Sir) Tim Berners-Lee
  • 1990 Internet service providers plus dialup groups AOL, Prodigy, …
  • 1993 commercialization and “Information Superhighway” (Al Gore)
  • 1995 commercial web servers and domain names grew, requiring search engines (Lycos, Altavista, Northern Light, …)
  • 1997 Google began selling behavioral data, “if you’re not paying for the product, then you *are* the product”

Everybody Welcome

  • 2000 dot-com bust focused capitalism
  • 2003 California Secretary of State survey of election systems (all failed)
  • 2004 Facebook started, money flowed into Silicon Valley,
  • 2016 Cambridge Anyltica/Russian UK and US election disruption
  • 2019 Summary “Surveillance Capitalism”, Harvard book by Shoshana Zuboff, explains economic logic: behavioral data produced in search and browsing become material processed to predict behavior; data that can be bundled and sold without regulation for targeted messaging, including product advertising and political information, creating , monopolies and disinformation risks. * Video Shoshana Zuboff explains “Surveillance capitalism”

Career Trail

ISI fun, verification research, safety and security applications. Email sgerhart@ISI-A 1977, 1980s Usenet groupie, 1993 web site, 1995 domain name, twURL search tool, 2004 paper “Do Search Engines Suppress Controversy?”,

Coordinates:, slger Susan G on Twitter and LinkedIn

Current Web sites:,,,, CatchTheVision.Life


  • Books: “Where Wizards Stay Up Late” by Katie Hafner; “Inventing the Internet” Janet Abbate; “Close to the Machine” (memoir) and “The Bug” (mystery) Ellen Ullman; “The Age of surveillance Capitalism” Shoshana Zuboff
  • Organization: Post Center and USC Information Sciences Institute reports and projects; Internet Society; IANA (Internet Assigned Name Authority); European Data Regulations
  • Podcasts: Cara swisher interviews; KQED Forum ( Michael Krasny); “Internet History”; “Function” by Anil Dash; …
  • Libraries: Wikipedia; Wayback Machine at Internet Archive San Francisco; Computer History Museum in Palo Alto; Babbage Institute (Minnesota); Internet Society Hall of Fame

Ada Lovelace: A Computational Thinker

Ada Lovelace: A Computational Thinker

Background:Child level biography TBD + YouTube “The Brilliant Life of Ada Lovelace

Family Facts

  • Father George Gordon, Lord Byron, “mad, bad, and dangerous”, poet, died age 36
  • Mother AnnaBella socialite, intellectual, studied math, “Princess of Parallelograms”
  • Half-sister, by Byron’s half-sister, later adopted by AnnaBella
  • husband William King, Lord Lovelace, nice guy, architect/developer
  • Son Byron (went to sea), daughter AnnaBella(raised Arabian horses), son Ralph (managed estate)
  • 10 living descendents
  • Health: often energetic, frequently sickly, bedridden with measles, cervical cancer at age 36, buried near Lord Byron

Ada’s Education

  • AnnaBella ruled: “mathematics, not poetry”, “control your imagination”
  • Best tutors money could buy
    • Augustus de Morgan, famous for law NOT (a OR b) = (NOT a) AND (Not b) symbolic logic
    • Mary Somerville, prolific science summarizer, philosopher
    • Independently Wrote imaginings of mechanical flying things
  • Ada toured Europe but remained “very British”
  • rumored teenage fling, tried to elope
  • AnnaBella introduced her to her adult contemporaries, took her to London
  • Ada met the Difference Engine at a Charles Babbage soiree
  • Lifetime friendship developed with 20 years older Babbage

Ada’s Imagination

  • What attracted her to math — was it equations, diagrams, puzzles, science applications, “truth”?
  • What attracted her to mechanical systems — action, stories, math, freedom?
  • Was she a “nerd”? did her image harm her life?
  • How did she survive misogyny of tutors? “women not up to math?, “too much excitement”, “harmed her health”, …
  • How was she affected by Romanticism?

Two Geniuses: Lovelace and Babbage

Who was Babbage?

  • Wealthy, no job, scrounged for grants, no deliverables
  • Industrial theorist, originated operations engineering, studied systems, theorized about automation and jobs
  • Invented cow-catcher, postage stamps, tables of logarithms, …
  • Loved parties, hated street musicians
  • Friends with Darwin, Dickens, and Cambridge University cohort
  • Worked in notations nobody understood, couldn’t find precise components, always improving on innovations, but one version exists (I saw it!)
  • Bad technology timing, poor manager, dreamer
  • Sparked 17 year old Ada interest in his machine dreams and models

170 years later, a Difference Engine at Computer History Museum

Pattern-driven Jacquard Loom Suggests Analytic Engine

YouTube demo of card-driven loom

  • Cards, rods, wheels spin patterns (hint of programs)
  • Punched cards used for data by Hollerith circa 1890 then IBM records for Nazis in WW II
  • Punched cards held programs until 1970s
  • Novice programmer lesson, 4 day wait for program rejected due to punch error

Ada Writes the 1st something

  • Babbage talks in Italy, mathematician writes a summary in French, ready to publish
  • Babbage asks Ada to translate, she expands with notes
  • She chooses Bernoulli numbers for example (sums of powers of integers)
  • Babbage and Lovelace check each other’s work
  • Women cannot publish, so author is “A.A.L”
  • Ada suggests to Babbage that she take over the Analytic Engine business as manager while Babbage engineers and builds, finally. Offer rejected.
  • Becomes interested in electricity, optics, and rainbows, praised by Faraday
  • Ada turns to betting on horses, pawns family jewels, leaves scandals

Ada’s Influence grows

  • She claimed “The Analytic Engine can do only what it’s told, cannot originate”
    1940s cryptographer and mathematician Alan Turing takes on “Ada’s Objection” and asks “Can computers think?”
  • 1970s International language for safety-critical systems is named Ada, now runs major aircraft, trains, regulated systems
  • USA then British adopt Ada as hero and model for STEM programs that raise money, “Finding Ada” October Ada Lovelace day newsletter, podcast
  • Lovelace papers public at Bodline library at Oxford, Difference Engine at British Museum

Ada’s Contributions

  • (Universality) “the Analytical Engine weaves algebraical patterns just as the Jacquard-loom weaves flowers and leaves” . The Analytic Engine can operate on not only numbers but also music, and symbols. (but how could she foretell modern “packets of data representing persons”
  • (Point of View) Ada wanted to create a “calculus of neurons” from knowledge about the brain and thinking,
    but could not imagine “fake news” and “political lies”.
  • Defined key ideas of programming
    • (Basic control structure of programming) The Analytic Engine could compute in loops under control of variables on punched cards rather than long sequences of operations
    • (Optimization) Her concept of loops could improve the programs for existing Jacquard looms.
  • (Originality and Exploration) The Analytic Engine assists, does what it’s told, cannot originate. However, assisting a scientist can lead to discovery and insight into the problem and solutions.
  • (Cooperation Wins) Lovelace brought a clear exposition to Babbage’s rambling models. Both spoke “math-ese” and enjoyed contemporary formulations of physical problems and theories. They corresponded freely without email or social media. Neither needed money to live on. Neither had the burdens of a job, e.g. meetings, colleagues. Both had meaningful family structures. Their minds abstracted differently, based on computational thinking. They partnered well.
  • (Multi-talented) Lovelace combined mature skills in math, language, abstraction, , explanation, calculation, carefulness, …
  • Summary: Ada Lovelace was an extraordinary Computational Thinker!

Readings and Videos

  1. Brief biography, emphasizing her work, mentioning gender issues
    Video YouTube “The Brilliant Life of Ada Lovelace”
  2. Babbage Difference Engine, imaginary then, cloned now.
    Video Babbage Engine at Computer History Museum, Mountain View CA
  3. Demonstration of the Jacquard loom
    Video Jacquard loom demonstration YouTube
  4. International Celebration, Ada Love lace Day, honoring women in STEM
    Event “Finding Ada October event in London for Women in STEM
  5. Novel “Enchantress of Numbers, by Jennifer Chiaverini. Including many letters, embellished portraits of William King and other family, mostly historical.
    Fiction Jennifer Chiaverini book site and blog
  6. Deeper story of technical accomplishments of Lovelace and Babbage
    Essay “Untangling the tale of Ada Lovelace by Stephen Wolfram
  7. A graphic novel heavily footnoted, with Wikipedia back story
    Fiction “Thrilling Adventures of Lovelace and Babbage” by Sydney Padua
Picture of Ada Lovelace

Long Quotations

Source: “Untangling Ada” by Stephen Wolfram

Good Work Habits Matter

“My Dear Babbage. I am in much dismay at having got into so amazing a quagmire & botheration with these Numbers, that I cannot possibly get the thing done today. …. I am now going out on horseback. Tant mieux.”

Later she told Babbage: “I have worked incessantly, & most successfully, all day. You will admire the Table & Diagram extremely. They have been made out with extreme care, & all the indices most minutely & scrupulously attended to.” Then she added that William (or “Lord L.” as she referred to him) “is at this moment kindly inking it all over for me. I had to do it in pencil…”

A Practical Proposal — Rejected

“Your affairs have been, & are, deeply occupying both myself and Lord Lovelace…. And the result is that I have plans for you…” Then she proceeds to ask, “If I am to lay before you in the course of a year or two, explicit & honorable propositions for executing your engine … would there be any chance of allowing myself … to conduct the business for you; your own undivided energies being devoted to the execution of the work …”

“Enchantress of” NUMBER

Babbage wrote “Enchantress of Number” and “my dear and much admired Interpreter”. (

Does “Enchantress of Number” differ from “Enchantress of NumberS”?

Mathematical Points of View

“It does not appear to me that cerebral matter need be more unmanageable to mathematicians than sidereal & planetary matter & movements; if they would but inspect it from the right point of view. I hope to bequeath to the generations a Calculus of the Nervous System.”


“We may consider the engine as the material and mechanical representative of analysis, and that our actual working powers in this department of human study will be enabled more effectually than heretofore to keep pace with our theoretical knowledge of its principles and laws, through the complete control which the engine gives us over the executive manipulation of algebraical and numerical symbols.”

A little later, she explains that punched cards are how the Analytical Engine is controlled, and then makes the classic statement that

“the Analytical Engine weaves algebraical patterns just as the Jacquard-loom weaves flowers and leaves” .

Computational Originality

“The Analytical Engine has no pretensions whatever to originate anything. It can do whatever we know how to order it to perform…. Its province is to assist us in making available what we are already acquainted with.”

(Later referred to by Alan Turing, circa 1934, as Lovelace’s Objection

Mathematician Stephen Wolfram’s Tribute

Note: Wolfram developed Mathematica, a symbolic math system, now extended to many applications and an app, Wolfram Alpha.

The story of Ada and Babbage has many interesting themes. It is a story of technical prowess meeting abstract “big picture” thinking. It is a story of friendship between old and young. It is a story of people who had the confidence to be original and creative.

It is also a tragedy. A tragedy for Babbage, who lost so many people in his life, and whose personality pushed others away and prevented him from realizing his ambitions. A tragedy for Ada, who was just getting started in something she loved when her health failed.

We will never know what Ada could have become. Another Mary Somerville, famous Victorian expositor of science? A Steve-Jobs-like figure who would lead the vision of the Analytical Engine? Or an Alan Turing, understanding the abstract idea of universal computation?

That Ada touched what would become a defining intellectual idea of our time was good fortune. Babbage did not know what he had; Ada started to see glimpses and successfully described them.

… But the challenge is to be enough of an Ada to grasp what’s there—or at least to find an Ada who does. But at least now I think I have an idea of what the original Ada born 200 years ago today was like: a fitting personality on the road to universal computation and the present and future achievements of computational thinking.

Susan L. Geerhart, for YC OLLI course on “Women of Imagination” with Carol Hammond covering oMary Shelley and the book/play/movie “Frankenstei”. Other topics include: Count Buffon, Thomas Jefferso, and the American “Degeneracy Theory”; the Tambora volcano eruption of 1815 and the ensuing climate disruptions; the beginning of the industrial age; and characteristics of imagination and creativity. October 31 2018-December 2018 Yavapai College OLLI (Osher Lifelong Learning Institute), Prescott Arizona


Learn Twitter: a Prescottt OLLI Workshop

Learn Twitter — OLLI Workshop Feb. 6, 2014 1-3 p.m.

Susan Gerhart, @slger123


  1. Vocabulary Literacy “follow @slger123” or “#madman”>
  2. Why millions use Twitter>
  3. Interfaces today EasyChirp and Twitterific iPhone app
  4. How to get started
  5. Gaining followers or building a community, if you want

Vocabulary and Concepts

  1. “Tweet” = 140 characters or less message sent from a user account
  2. “timeline” = reverse chronological list of tweets from users you follow
  3. “to follow=act of adding user to receive tweets from, “unfollow”=act of ceasing to follow
  4. “followers” =list of users who followeach user , “following” = list of accounts followed by a user
  5. “user”/account = person, company, product brand, fake person, news outlet, …
  6. hash tag= term in message marked with # to cluster tweets
  7. “link” = URL within a tweet, which apps display
  8. “direct message”=private message sent between users who follow each other
  9. “retweet”=send a tweet from another user to your followers
  10. “mention”=se @user in a tweet, e.g. retweet or reply
  11. “list”=subdivision of followers or following list to show in timeline
  12. “trending”=hashtags with growing popularity

More advanced and problematic

  1. NO privacy, all tweets, follower and following lists are public
  2. “retweet retreat”= undoing a bogus or mistaken retweet
  3. twibel”=maybe libelous tweet, to be adjudicated
  4. WTF, OMG, ROTFL … and offensive terms, no censorship
  5. spam = follow somebody to tell them you have a dandy product or service
  6. “block”=stop a user from following, “mute” within an app stop show tweets for a time period
  7. “tweetup”=face-to-face with people you tweet with
  8. “Promoted”=tweets with ads to sustain Twitter revenues
  9. Remember in social media “If you are not paying for the product then *you* are the product!”

Why Use Twitter?

  1. Newsline for breaking news, columnist posts, background, announcements, …
  2. Promotion and feedback, e.g. authors, celebrities, politicians, …
  3. Organization newsletter briefs, e.g. AAUW, Prescott Film Festival, alumni groups, …
  4. Special informal communities, e.g. petitions, jobs, interested in how blind people use computers, #accessibility or #a11y

  5. Fun and parody, e.g. @BronxZooCobra, @InvisibleObama, @FakeSteveJobs
  6. Emergency networks, e.g. Boston marathon bombing, Amber alerts, political revolutions, …

Getting Started

  1. Sign up at, write your profile, do not provide contact list, get popular people to populate your timeline
  2. Pursue an interest, e.g. author, TV show, magazine, hobby, local business, …
  3. Add a few followers at a time, view and add from Following list of users you like
  4. Experiment with interfaces, e.g. or EasyChirp , or smart phone apps like free Twitter or cheap Tweetlist or Twitterific
  5. Do not try to read whole Timeline, e.g. sample 30 minutes twice a day
  6. Unfollow freely, following is not usually friendship
  7. Use app “search” to find and save tweets of interest, e.g. “yarnell fire” or “football concussions”
  8. Snag @user from just about any web page
  9. Give yourself two months to learn to use tweets, find a comfortable app, evolve interests
  10. Follow @SeniorSusan for lists of local interest, including OLLI, and senior needs and wants

Build your Followers

  1. Listen, learn, then “Join the conversation”
  2. Find people or groups who value your announcements or advice or recommendations
  3. People you follow may get a message or see you on the list or notice a mention and Follow you back>
  4. Be smart, polite, terse, informative or however you project your persona
  5. Tweet occasionally but not too much
  6. Use Lists to group meaningfully, others will find your List
  7. Add your @User to email, web page, …
  8. Go to a tweetup to meet people with common interests

Course Description

G) Learn Twitter : Discover, Connect,Communicate

Thur, 2/6 ONLY, 1-3pm, Bldg: 31, Rm: 105
Facilitator: Susan Gerhart Limit: 30

Twitter is the social network based on 140 character messages.
First, learn the vocabulary “tweet/re-tweet,” “follow,” and
“hashtag.” Then set up an account at and find an application
or free mobile app you like. Identify people, organizations,
or publications that interest you to follow. Speak up when
you’re ready and find your own followers, i.e. “join the conversations.”
We’ll explore typical virtual communities of book authors,
breaking news, Apple Keep an Open Mind, and follow the seeing
eye of slger123 with 450 followers, following 650, and over 2000

This page is available at “”