Updating Our YC OLLI Learning

Here’s a way to celebrate OLLI classes, facilitators, and discussions.

YC OLLI members are welcome to use this website to share interesting articles and audio related to their OLLI classes over the past 25-plus years. Here’s the deal:

Mechanically, you enter a few lines into the comments section of this post then it appears after a few hours for moderator approval. Fill in the name and website fields with your information if you want it known, or just make up something. Please explain your link in a sentence and relate it to OLLI classes and facilitators, as your memory permits.

Here are prohibitions. 1) Mis-information; 2) Advertising; 3)links to Facebook; 4) requiring a password, including EDU/CharlieBrown/whatever; 5) silent audio’s and unexplained graphics. Corrections and comments on other comments are welcome.

I, Susan L. Gerhart, member since 2008, will try to post daily from my information consumption. Think of your favorite OLLI classes and read up on something related. Read an article somewhere and hark back to OLLI classes and facilitator wisdom that helps you understand the article’s topic. Controversies are welcome if rooted in an OLLI class. Continue your OLLI learning.

This website contains material I’ve used in classes I co-facilitated. You’re welcome to learn more about Twitter, podcasts (my favorite medium), Ada Lovelace, climate fiction, or the Singularity.

This page is not officially part of the “new OLLI” technology strategy, just how the Web should be used, openly and interactively.

slger123@gmail.com(and beautiful guide dog Corky).

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 QuantifiedMe.com 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=”https://www.youtube.com/watch?v=MXHL89PDHAc”>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: slger123@gmail.com, slger Susan G on Twitter and LinkedIn

Current Web sites: AsYourWorldChanges.wordpress.com, YCOLLIAsks.wordpress.com, AChipOnHershoulder.com, twURL.com, 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 https://twitter.com/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 Twitter.com, 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. Twitter.com 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 Twitter.com 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 “”

Anthology of Climate-based stories, edited by John Joseph Adams

Climate-Centered Fiction — 2018 Spring 1

Climate-Centered Fiction — Prescott OLLI, Spring 1, 2018

Course Description

4)Climate-Centered Short Stories
Wed, 1/31-3/7, 2:30-4:30pm
Bldg: 30, Rm: 126 Limit: 14
Facilitator: Susan Gerhart

We will read short stories from an anthology,
Loosed Upon the World, edited by John
Joseph Adams (available on Amazon for
about $10). Icebergs, rising seas, population
migration, water wars, animal mutation, seed
vaults, drought, smog, carbon re-absorption,
entangled technology, and many more
climate-based situations force humans into
action in the near future. For example, how
does an Everglades community decide its fate
as seas rise?

We’ll learn more about climate
science and societal adaptations happening
now. Several story authors are well known
in science fiction. Stories are empathetic,
down to Earth with human characters. Some
geographical settings are nearby. We’ll also
sample contemporary actions from the
America Adapts podcast and the ASU Climate
Futures Initiative.


Anthology of Climate-Situated Short Stories

Short Story Collection “Loosed Upon the World” edited by John Joseph Adams ,
See Synopses Below … Categorized as Resistance, Mitigation, Adaptation…

Schedule for Reading

  1. January 31
  2. February 7
  3. February 14 — Class Selections
  4. February 21
    Class Selections
  5. February 28
    Class Selections
  6. March 7
    Class Selections
    1. Novella “Entanglement”, Vendana Singh

Questions for Discussion — Climate-Centered Fiction

  1. What year (approximately) does this story take place? What has changed between now and then?
  2. What did you like or dislike about the story itself? its characters, plot, description, motivation?
  3. What’s the scientific explanation for the climate situation?
  4. How effective are the stories actors and actions for Resistance/Mitigation/Adaptation/Other goals?
  5. How has the story’s climate situation affected countries, communities, families, individuals? also institutions, education, capitalism, democracy, other?
  6. What would *you* do if placed in this situation?

If you find good resources for this discussion, please add as comments on Links for Climate-Based Stories at https://YCOLLIAsks.wordpress.com.

Stories — Synopses

THEME: Adaptation


The US Capitol floods, oceans stall, ice sheets melts, so Big Science and Engineering to rescue.

Science — rains/tides, warming, ocean currents, NSF; Engineering — marine rescues, ocean salting, sea drainage, forest renewal; Social — climate friendly policies, science management, forceful response .


A flooded Everglades community evaluates its options.

Science — slowly rising seas, mind-enhancing drugs; Engineering — dredged islands, floating houses; Social — public services, coastal capitalism, financial pressure.


Mutiny and a captured iceberg challenge a ship captain.

Science — melting icebergs, squid, sun rays, drought; Engineering — grappling an iceberg, squid fishing, sun screen; Social — iceberg markets, sunscreen rationing, climate justice .


An agricultural economy adapts to flooding.

Science — soil erosion, plant biology, poultry behavior, buoyancy; Engineering — dams, indigenous industrial practices, material engineering; Social — cultural memories, industrial scale, alternative economies.


A fight erupts over the management of a Siberian-based tower of machinery for carbon re-absorption.

Science — healthy forests, carbon recycling; Engineering — tower of atmospheric machines, grounds of forest and vaults; Social — climate-based capitalism, family turmoil,, international resource usage.


A town experiences submersion and population loss.

Science — rapid sea rise; Engineering — sea walls, tracking sea rise; Social — small town, family stability, sea rising rituals.


A smog-ridden Asian city explores causes and correlations of smog and mental conditions

Science — smog conditions, smog data, effects on humans; Engineering — smog particulate measurements, resistance; Social — depression, family planning, resistance, children.


A marooned community springs up in the Astrodome after Houston floods.

Science — extreme weather; Engineering — structural reconstruction, waste management (think Katrina); Social — community organization, will power, applied expertise.


Scientists and capitalists explore uses for a melted Greenland.

Science — ecology of frozen land, changes over eras, glacier melt-off raising sea levels; Engineering — melt-off lake, outflow electricity generation; Social — science mentors, elder wisdom, capitalist secret plans, terrorism.


Renowned Dutch dike Engineering faces deeper challenges.

Science — water level predictions; Engineering — dikes, moveable barriers, engineer training; Social — public services, risk management, climate careers, family pressures.

THEME: Mutation/Evolution


The thrilling adventures of the Russian mafia, a female scientist, and a buccaneer to save plant DNA from greedy exploiters of climate change.

Science — plant extinction, DNA sequencing, marine health; Engineering — chem trails, marine salting, iceberg harvesting, plant seed protection; Social — international agriculture competition, climate-based economy, climate-related treasure.


Uranium mining and major flooding change lives for a Grand Canyon park ranger and her gadget-driven young niece.

Science — species mutation, omnivore-carnivore preferences, Southwest flooding; Engineering — toxic mines, Grand Canyon adjustments, wearable film-making; Social — inter-generational customs, naturalist careers, tourism/entertainment.


The moody ocean affects a family inheritance.

Science — Ocean GMO, micro-burst, atmospheric tripping; Engineering — resilient housing, chemical weather prediction; Social — coastal planning, family interactions, climate careers.


An oxygen-rich environment is great for bugs, not so much for humans.

Science — rapid species change, oxygen imbalance; Engineering — specialized extermination procedures, insect barriers; Social — family fears, military oversight.


Rain dances, pyrotechnic lightning, military operations, fast cars, flash flood, religious ritual = ???

Science –; Engineering –; Social — .

THEME: Resistance


A drought-stricken farming community battles the Southwest for its fresh water.

Science — rapid drought, diminishing Great Lakes water supply; Engineering — long-distance water transport; Social — despair, poverty, terrorism.


Making a living off another territory’s water flowing through an empty landscape.

Science — drought period, invasive plants; Engineering — capped wells, plant bounty, long “straw” pipe; Social — abandoned towns, water ownership, bounty hunting.


An eco-activist struggles to help an owl amid an invasion of well-off refugees into the still-rainy Northwest.

Science — species DNA, forest ecosystems; Engineering — zoos for life extension, capture and preserve techniques; Social — income inequality, wealth preservation, eco-system policies, eco-activism.


A family fleeing the coastline into the interior encounters an epidemic beyond CDC help.

Science — rapid sea rise, malarial disease; Engineering — refugee boundaries, CDC management; Social — Samaritan mistake, child-adult trust, epidemic spreading, inland demographic change.


An eco-researcher games a climate change simulation contest.

Science –Climate models, atmospheric data, human intuition; Engineering — cyber security, simulation; Social — family conflict, competitive drive, academic gamesmanship, serious games .


A frivolous technology company shows its stuff.

Science — mostly IT; Engineering — wearable devices, automated cars, product development; Social — nonprofit vs startup, interventions, buyer strategy .


An atmospheric operation over the Arctic is challenged, para-military style.

Science — hydrogen sulfate, sun reflection; Engineering — airborne operations (Anchorage), logistics management, weapons; Social — fossil activism, military/paramilitary cultures, Inuit natives, bird watching.


inter-generational warfare around a tipping as Judgement Day for ignorance, waste, and opposition.

Science — tipping point model, human-caused warming; Engineering — evidence for judgements, Climate-based -torture; Social — cause-effect blame, younger pay back, self-defense, nasty, nasty.


Texans migrating to Arizona receive a raw welcome.

Science –drought; Engineering — water transfer projects,; Social — journalism, migration, boundaries, poverty, guns, housing.



A parable for the apocalypse.

Science –; Engineering –; Social — .


A novella of a social network helping others across Siberia, Brazil, India, Midwest US, and Tibet.

Science — methane, landslides, tornadoes, gardens, whales; Engineering — wearable network device, methane-eating bacteria, roof gardens, wall art, education; Social — citizen science, retirement resistance, art attraction, ancient wisdom, careers.

<h3Table of Contents — Loosed upon the World

  1. Introduction JOHN JOSEPH ADAMS


Book “Loosed Upon the World”

Book Website: Loosed Upon the World

About Climate Change


About Climate Fiction

Contacts and Links

Podcast Listening for Fun and Learningx

Podcast Listening for Fun and Learning

YC Prescott OLLI Workshop, June 15 2015

Susan L. Gerhart, slger123@gmail.com

This page at http://YCOLLIAsks.wordpress.com


  • Podcast* is _________
  • The underlying Podcast* Internet technology is _________
  • One benefit of using Podcast* is _________
  • To use Podcast*, I will need _________
  • A famous podcast* is _________
  • To use podcast*, I will have to give up
  • I will know I am a podcast* addict when __________________
  • One way to use Podcast* in OLLI is _________
  • Podcast* fits the OLLI mission by _________

  1. The destination is a satisfying podcast listening experience.
  2. Your path will vary: what, when, why and how.
  3. Go home and experiment.

Podcast* Jargon

    Podcast media file = e.g. *.mp3
  • Podcast feed or subscription, = source
  • Podcast episode = one Podcast file, one in a subscription list
  • Podcasting = preparation and delivery of Podcasts
  • Podcatcher = podcast retriever/player
  • Podcast app = program on Android or iPhone
  • Podcast network = coordinated group of podcast subscriptions
  • The PubSub Model

    • Publish = make known the location of a podcast episode
    • Subscribe = make a podcatcher know about the address of a Podcast Feed
    • update = command a podcatcher to retrieve newly published podcast episodes for its subscriptions

  • Retrieval

    • Download = fetch a podcast file to your device
    • Stream = play remotely but not save a file

  • Show notes = text accompanying a podcast episode, e.g. summary and links
  • Play list = list of podcast episodes within a player
  • OPML = files of podcast feed information for sharing among apps

The Podcast Model


  • Publish/Subscribe, PubSub
  • RSS (Really Simple Syndication), also for news, blogs, updates,…


  • Public network subscriptions NPR, PRI, … donations
  • Advertising
  • Promotion of a product or service or person
  • Hobby sharing
  • Community, e.g. low vision
    Networks of podcast feeds: Slate/Panoply, RadioTopia, WNYC Comedy, , spin offs of popular shows, …

  • continuing education: medical technical, , tec


  • Live shows, g. g. Apple keynotes
  • Interviews
  • Gabfest or Roundtable
  • Demonstrations, Tours
  • Serial of fiction or nonfiction
  • Lectures


  • Older than 10 years, since 2003
  • 1000s of sources, see directories
  • ?? listeners, millions for “Serial”, a crime investigation
  • ???$$$ advertising, defined markets, no tracking


  • Public radio/TV: Diane Rehm,60 Minutes, Wait Wait, …
  • Independent News: Democracy Now,
  • Magazines: The Economist, New Yorker, Slate, ,
  • Science: Inquiring Minds, Radio Lab, Science Friday, Nature, …
  • Technology: Mac Roundtables, NosillaCast, Mindful Cyborgs, , Future Tense, Reply All, Note To Self,
  • Economics: The Economist, Slate Money, Econ Talk, Freakonomics, …
  • Culture: Slate Culture, Stuff Mom Never Told You, Slate Parenting, …
  • Politics: Slate Politics, Supreme Court; Democracy Now,
  • Books: Books on the Nightstand, BBC World book Club, Slate Book Club, Grammar Girl, KQED/Rehm interviews, …
  • Critical Thinking: NPR Intelligence Squared, Counter Spin, On the Media, …
  • OLLI relevant: The Torch, Inquiring Minds Essential Science Professor, TED Talks (video, audio, NPR), Intelligence Sq debates, …
  • Low Vision: Apple Vis, Main Menu, Hadley School tutorials, Blind Cool Tech, Blind Film Critic, Movies for Blind, Eyes on Success, …

Example: Listening on iPhone

  • Choose a podcatcher: iCatcher …
  • Subscribe to podcasts you want from a directory or typed in feed addresses
  • Develop a schedule to Download

    • Batch, all subscribed
    • Individual podcast subscriptions
    • May choose from list available or download all
    • Podcatcher may have a scheduler, e.g. every 6 hours

  • Listen when and where you want

    • Individual episodes, pause, discard, mark to save
    • Define play lists, e.g. news, daily, tech, …
    • Move files to another device
    • Use speakers, ear buds, or audio devices like cars

  • Clean up often

    • 30 MB average per episode adds up to GB quickly!!!
    • Discard immediately or mark to save or move to save or …

What could go wrong?

  • Run out of disk space, so clean up often
  • Cellular bandwidth costs soar, so use home WIFI for downloading
  • Run out of time to listen, so change your habits
  • Choose wrong app, so start with just a few subscriptions, read reviews
  • Too many subscriptions, so prioritize
  • Got hooked, so too bad
  • Episodes too long, so manage time differently, stop early, speed up to 2x
  • Security, need a credit card to buy apps, so use a special one for online
  • Security, password stolen, so don’t use un trusted WIFI
  • Privacy, downloads not tracked, but saved files tell your tales
  • foul language, so often a disclaimer
  • Misinformation, welcome to the new media

Finding your app

Use this service to find Descriptions of and alternatives to many podcatchers at http://alternativeto.net

  • iPhone/iPad/iPod: iCatcher, DownCast, OverCast, Podcasts
  • Android: DogCatcher, Beyond Pod, Podcast Addict, Podcast Republic
  • Windows: iPoddder/Juice
  • iTunes
  • Stitcher, everywhere

What next?

  • Experiment!
  • Questions or suggestions on YCOLLIAsks website comments
  • Integrate into OLLI courses
  • Grown younger, wiser, and “contribute to a rapidly changing multi-cultural and multi-generational society” (OLLI mission)

Susan Gerhart, slger123@gmail.com Comments welcome at http://YCOLLIAsks.wordpress.com
June 2015

Lively Science and Technology Topics from OLLI Learning Groups

Where does Moore’s Law lead? to the “Singularity”? When?

How will 3d printers revolutionize manufacturing?

How has Twitter changed news distribution?

Did science and technology play a role in the 2012 elections?

Who invented the Internet?

How do visually impaired people live? Using Things That Talk!

Do we citizens really need to worry about cybersecurity?

Is Prescott OLLI online? Yes, http://yc.edu/prescottolli

Day 6 May 10 What Could Go Wrongg?

Countering the Singularity and Abundance Scenarios

What could block the abundance and singularity futures?

  1. Catastrophes system failures, e.g satellite destruction, see “Sky alert” or Bill Joy “gray goo” or uncontrollable climate change
  2. Unabomber social backlash
  3. Big science snafu, e.g. brain, nanotech, big data
  4. Cost exhaustion, e.g. market crash, Medicare costs, wars
  5. Terrorism due to loss of meaningful work

  6. Crackpot ideas and leaders, e.g. Kurzweil, Diamandis, Drexler, …
  7. Information pollution, e.g. malicious, filter bubble, …

Day 5 May 3 The Singularity-Abundance Arguments

  • “Abundance” by Peter Diamandis, 2011
  • “How to create a mind: the secret of human thought revealed” by Ray Kurzweil, 2012
  • ?”Transcendent Man” documentary 2009

Conclusions and Predictions

  • *WE* can live forever (sort of) 2045
  • Brain backups should be routine 2029
  • Humans will admit artificial intelligent beings as equals 2030s
  • New ways of producing energy will mitigate climate change 2030
  • Almost all literature will be digitized and understood by artificial intelligence’s 2020
  • Nongovernmental technologists will mitigate many world maladies NOW Singularity U
  • Abundance attitudes will transcend cynicism 2014


  • Laws of Accelerating Returns, linear versus exponential thinking
  • DIY movement and manufacturing revolutions empower including “rising billions”
  • Government-independent wealthy techno philanthropists are addressing world challenges
  • Tools of Cooperation energize and connect traditional technologists and the “rising billions”
  • Education and daily lives are dependent on integrated crowd source Knowledge services using contextual reasoning for retrieved content
  • Accelerating medical market changes LOC (lab on a chip), remote diagnosis, assistive robots (Herb), 3d printed organs, nanobot body monitoring, …
  • Electric cars, non-lithium batteries, smart grid,oil-producing algae, Internet of Things (industrial Internet)changing energy industries
  • Conversational practices are diversifying and accelerating, e.g. texting, speech recognition, text to speech, chatbots, …
  • Knowledge processing intelligence’s are modifying professions, e.g. Watson on Jeopardy and medicine
  • Entertainment is education and vice versa, e.g. games, crowd sourced protein folding, iCivic.org, …
  • “news poisoning” recognition and reversal are modifying journalism global and accelerating
  • scientists are strengthening nanotechnology and genetic capabilities

Kurzweil future Thinking: reverse engineering the brain

  1. Proven models in text and speech recognition (Nuance, Siri)
  2. PRTM (Pattern Recognition Theory of Mind) derived from recognition technologies: hierarchy, redundancy, prediction, shared links, likelihood, neuroplasticity, 300 million patterns
  3. Non-invasive brain mapping projects “moon shot” to identify data to export
  4. Memories are reconstructed patterns, reduce redundancy and diminish power over time, maintained by neuroplasticity and training
  5. Exponential progress will allow extraction and storage of brain pattern info on external drives
  6. Increasingly memories and pattern data are stored in the “cloud” and services like Wikipedia
  7. “Transcendent Man” dream reachable

Disputes and debates (day 6)

  1. Bill Joy “The Future Does Not Need Us” “Gray goo”, and other GNR perils …