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.”

Universality

“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

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Learn Twitter: a Prescottt OLLI Workshop

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

Susan Gerhart, @slger123 https://twitter.com/slger123

Overview


  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
tweets.



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.

Readings

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
    1. RACING THE TIDE, CRAIG DELANCEY
    1. STAYING AFLOAT, ANGELA PENROSE
  2. February 7
    1. THE TAMARISK HUNTER, PAOLO BACIGALUPI
    1. MUTANT STAG AT HORN CREEK, SARAH K. CASTLE
  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

TRUTH AND CONSEQUENCES, KIM STANLEY ROBINSON

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 .

RACING THE TIDE, CRAIG DELANCEY

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.

HOT SKY, ROBERT SILVERBERG

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 .

STAYING AFLOAT, ANGELA PENROSE

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.

KHELDYU, KARL SCHROEDER

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.

QUIET TOWN, JASON GURLEY

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.

THE SMOG SOCIETY, CHEN QIUFAN

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.

EIGHTH WONDER, CHRIS BACHELDER

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.

THE SNOWS OF YESTERYEAR,JEAN-LOUIS TRUDEL

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.

THE NETHERLANDS LIVES WITH WATER, JIM SHEPARD

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

MITIGATION, TOBIAS BUCKELL & KARL SCHREDER

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.

MUTANT STAG AT HORN CREEK, SARAH K. CASTLE

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 RAINY SEASON, TOBIAS S. BUCKELL

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.

THAT CREEPING SENSATION, ALAN DEAN FOSTER

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.

HOT RODS, CAT SPARKS

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

Science –; Engineering –; Social — .

THEME: Resistance

A HUNDRED HUNDRED DAISIES, NANCY KRESS

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.

THE TAMARISK HUNTER, PAOLO BACIGALUPI

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.

THE MYTH OF RAIN, SEANAN MCGUIRE

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.

OUTER RIMS, TOIYA KRISTEN FINLEY

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.

OUTLIERS, NICOLE FELDRINGER

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 .

THE DAY IT ALL ENDED, CHARLIE JANE ANDERS

A frivolous technology company shows its stuff.

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

EAGLE, GREGORY BENFORD

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.

THE PRECEDENT, SEAN MCMULLEN

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.

SHOOTING THE APOCALYPSD, PAOLO BACIGALUPI

Texans migrating to Arizona receive a raw welcome.

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

UNIFYING THEME: Worldwide

TIME CAPSULE FOUND ON THE DEAD PLANET, MARGARET ATWOOD

A parable for the apocalypse.

Science –; Engineering –; Social — .

ENTANGLEMENT, VANDANA SINGH

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
  2. FOREWORD, PAOLO BACIGALUPI
  3. SHOOTING THE APOCALYPSD, PAOLO BACIGALUPI
  4. THE MYTH OF RAIN, SEANAN MCGUIRE
  5. OUTER RIMS, TOIYA KRISTEN FINLEY
  6. KHELDYU, KARL SCHROEDER
  7. THE SNOWS OF YESTERYEAR,JEAN-LOUIS TRUDEL
  8. THE RAINY SEASON, TOBIAS S. BUCKELL
  9. A HUNDRED HUNDRED DAISIES, NANCY KRESS
  10. THE NETHERLANDS LIVES WITH WATER, JIM SHEPARD
  11. THE PRECEDENT, SEAN MCMULLEN
  12. HOT SKY, ROBERT SILVERBERG
  13. THAT CREEPING SENSATION, ALAN DEAN FOSTER
  14. (Novella) ENTANGLEMENT, VANDANA SINGH
  15. STAYING AFLOAT, ANGELA PENROSE
  16. EIGHTH WONDER, CHRIS BACHELDER
  17. EAGLE, GRGGORY BENFORD
  18. OUTLIERS, NICOLE FELDRINGER
  19. QUIET TOWN, JASON GURLEY
  20. THE DAY IT ALL ENDED, CHARLIE JANE ANDERS
  21. THE SMOG SOCIETY, CHEN QIUFAN
  22. RACING THE TIDE, CRAIG DELANCEY
  23. MUTANT STAG AT HORN CREEK, SARAH K. CASTLE
  24. HOT RODS, CAT SPARKS
  25. THE TAMARISK HUNTER, PAOLO BACIGALUPI
  26. MITIGATION, TOBIAS BUCKELL & KARL SCHREDER
  27. TIME CAPSULE FOUND ON THE DEAD PLANET, MARGARET ATWOOD
  28. AFTERWORD: SCIENCE SCARIER THAN FICTION, RAMEZ NAAM


Resources

Book “Loosed Upon the World”

Book Website: Loosed Upon the World

About Climate Change

Arizona

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

Basics


  • 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

Technology


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

Business


  • 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

Formats


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

Numbers


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

Examples


  • 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

Observations


  • 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 …






Day 4 April 26 “Information Abundance”?

Day 4 April 26 “Information Abundance”?

Rapid Accelerating change in the news industry – Barbara

See links below

Personal News Management and Information Literacy Susan



  • “If you are not paying for the product then YOU are the product”
  • “If you want 10,000 answers for a question, ask Google. If you want the best answer, ask a librarian”

Personal News Management


  1. RSS (Really Simple Syndication) and Pubsub model (Publish -Subscribe): automated updates
  2. Blogs (weblogs):journals, essays, news

    • Podcasts, as “audio blogging”, using RSS and podcatchers or iTunes

    • News readers, live feeds, former Google Reader and browsers

  3. Micro-blogging, e.g. Twitter

    • Tweet, 140 chars, including links
    • Follow, ask to receive tweets, hence “following” and “followers”
    • Timeline of tweets from those you follow
    • Retweets, hence “mentions”
    • Hashtags, #a11y or #boston, for trends, communities, brands
    • Clients: Twitter and Easychirp.com on web, Tweetdeck etc on PC and Mac, Tweetlist on IOSYahoo and Google
    • Start by following magazines, personalities, newspapers, etc to find what’s worth following, gain followers by worthy contributions or “follow me on Twitter”
    • Tweetups, people who tweet together have a community meet up

  4. Alerts, e.g. scheduled Google searches
  5. Groups, Usenet before web, Yahoo or Google etc.
    <LI<Facebook, all of above in a "walled garden"


SLGER123 profile: read 200 blogs via RSS; follow 500 on Twitter for news, books, tech products, especially #accessibility and blind community; 450 followers, some respond; 100 podcasts, e.g. DRSHOW, skeptics, vision support; 10 groups and mailing lists, e.g. systers and mdlist; “As Your World Changes” blog; YCOLLIAsks course record; stay in EasyChirp, Tweetlist,, downcast and iCatcher apps plus Levelstart (free news and book sources);Daily Courier via RSS; really want a community calendar like “Elm City” project

Value of Social Media Driven Personal News Management


  • Pick your sources, DIY reading and listening channels
  • Join and buildcommunities, e.g. accessibility, vision support, …
  • Lifelong learning on new topics, also memory and attention techniques
  • Brain Protection” avoiding shocking sources, time wasters, …
  • Bias avoidance from “filter bubble” and unconscious preferences

Information Literacy Exercise

What sources would you use for a 45 minute presentation to an educated but unfamiliar audience?


  1. MOOC (Massive Online Open Courses)s and Higher Education
  2. Understanding autism
  3. M anaging Yavapai region water resources

Day 3 April 19 3D Printers and Health

Day 3 DIY Manufacturing and Health

DIY = DO IT YOURSELF

Review: The 3D printer Process


  1. Buy a printer including book and training
  2. Assemble and test at home
  3. Join a club
  4. Define your thing to print
  5. Get shared designs from ThingiVerse, design yourself, or scan in definition
  6. Load filament and push MAKE
  7. Wait then toss or use, iterate
  8. Or send to Staples or ShapeWays for replication or distribution
  9. Pay for lunch on proceeds,

The DIY Movement


  • All Humanity crafts, agriculture, fixer-upper, etc.
  • 1970s “Whole Earth Catalog” – Motto?
  • also early PC clubs and garages
  • 1980s and 1990s additive and subtractive manufacturing, CNC, CAD, …
  • 2000s Make magazine, Maker fairs,
  • Less costly and more powerful personal 3D printers
  • also “open source” and sharing designs
  • 2012 “Makers” book Chris Anderson Wired writer and DIY drone entrepreneur
  • and marketplace Staples, Shapeways, ThingIVerse, Makerbot

Abundance and Singularity Theme


  • Expand and realign invention and manufacturing
  • Democratization: Anybody/everybody can play, including “rising billions”
  • Brings solutions closer to problems and provide more powerful problem solving tech
  • Build on Cooperation and Communication abundance to form better teams
  • A fast paced industrial revolution?
  • Nobody knows where this will lead!

DIY Exercise


  1. OVC Incubator looking for 3D printer projects
  2. Quick ideas: What’s your thing?
  3. Elevator pitch (15 seconds) : the thing, its users, justify big need
  4. We’ll get back to you

Day 2 April 12: Artificial Intelligence and Nanotechnology

Hour 1: AI, Robotics, and Pattern Recognition

What is “intelligence”?

Definition from 1960s by John McCarthy: If you see a machine doing a that you would consider intelligent if performed by a human”… not necessarily the same way

  • bird soaring over the ocean
  • reading and storing facts from Wikipedia articles
  • telling the denomination of a crumpled $10 bill
  • separating without ruining an OREO cookie
  • playing checkers, chess, bridge, …
  • exchanging traditional speech segments in a”conversation”

Watch these: robot tern, Watson/Jeopardy, robot butler, chatbot, iPhone app

“Turing Test”

when humans cannot tell if a conversational partner is human or machine

  • Coined by Alan Turing, WWII crypto hero mathematician
  • An actual annual contest, the Loebner prize
  • “Chatbot” technology, text conversations, support desks, iPhone apps
  • Technologies: synthetic voices (TTS, text-to-speech), speech recognition (speech to text), and natural language processing (text to meaning), expressiveness (cultural fitness)
  • DEMONSTRATION: Scottish voice Heather in a London art performance experiment

Robots


  • Things that move for a purpose
  • examples: industrial automobile assembly, Roomba vacuum, UAV/drones, surgical tools, …
  • Very hard to emulate humans with evolved brains and muscles
  • DEMONSTRATION: Pittsburgh Quality of Life Herb, personal assistant

IBM Watson vanquishes humans on Jeopardy


  • Lots of facts and associations, some gleaned from “reading” Wikipedia
  • NOT voice recognition, read text of questions
  • Used “statistical” reasoning, voting on certainty results from subordinate processors
  • Bank of coordinated memory, computation, and communication components
  • DEMONSTRATION Youtube of Jeopardy, recent vanquished Ken Jennings on TED

Pattern Recognition


  • Extract meaning from world objects to …
  • Examples: Vision senses, optical character scanning to text, …
  • Uses “algorithms” and “heuristics” (guessing)
  • DEMONSTRATION: LookTel Money Reader on iPhone and iPod Touch. How does this recognize patterns? Can you fool it?
  • DEMONSTRATION Siri, on iPhone ??? Google on Android phones

Implications of AI, Robotics, Pattern Recognition


  • Subject to exponential progress, law of accelerating returns
  • Improvements compound, e.g. Internet monetizes chatbots and apps
  • Feedback cycles accelerate progress, 1000s of users
  • When is the next “Intelligence Explosion”? Watson for medical diagnosis, water supplies worldwide, synthetic voices everywhere, takedown banking or electrical grid?