High School students are expected to know the content of the Massachusetts Mathematics Curriculum Framework, through grade 8. Below are skills from the framework that students have the opportunity to apply:
Construct and use tables and graphs to interpret data sets.
Solve simple algebraic expressions.
Perform basic statistical procedures to analyze the center and spread of data.
Measure with accuracy and precision (e.g., length, volume, mass, temperature, time)
Metric system: Convert within a unit (e.g., centimeters to meters).
Metric system: Use common prefixes such as milli-, centi-, and kilo-.
Use scientific notation, where appropriate.
Use ratio and proportion to solve problems.
Conversion from Metric-to-Imperial (English) and Imperial-to-Metric (taught this year)
Dimensional analysis (taught this year)
Determine the correct number of significant figures. (taught this year)
Determine percent error from experimental and accepted values.
Use appropriate Metric units, e.g. mass (kg); length (m); time (s); force (N); speed (m/s), etc.
Use the Celsius and Kelvin temperature scales
2016 Massachusetts Science and Technology/Engineering Curriculum Framework
Apply ratios, rates, percentages, and unit conversions in the context of complicated measurement problems involving quantities with derived or compound units (such as mg/mL, kg/m 3, acre-feet, etc.).
National Council of Teachers of Mathematics
Students need to develop an understanding of metric units and their relationships, as well as fluency in applying the metric system to real-world situations. Because some non-metric units of measure are common in particular contexts, students need to develop familiarity with multiple systems of measure, including metric and customary systems and their relationships.
National Science Teachers Association
The efficiency and effectiveness of the metric system has long been evident to scientists, engineers, and educators. Because the metric system is used in all industrial nations except the United States, it is the position of the National Science Teachers Association that the International System of Units (SI) and its language be incorporated as an integral part of the education of children at all levels of their schooling.
Teaching coding:3 Steps to Becoming a Coding Teacher, By Grant Smith
2. Prepare Yourself and Your Classroom
Notice how I included resources above for adults to learn coding. That means you! I recommend that you first review your selected curriculum and then move on to the more complicated stuff. I highly recommend the Intro to CS and Intro to Programming courses on Udacity. You should also prepare for your class by answering the following questions:
- What are your learning expectations for the students? (Check out these learning outcomes for the Khan Academy course as an example.)
- Are your students learning computational thinking, computer science, or computer programming? (There is a difference. Check out Harvard research on computational thinking.)
- What’s your classroom layout? (See my post for ideas.)
- Will your students work at their own pace or at your pace?
- Will students work through a curriculum, or will it be project based?
- How will students collaborate?
- How will students share their work with you, their peers, and the world?
- How will student accounts be managed? Will you create them? Do you need parent or administrator permission?
- Why should your students learn to code? (Students are more excited to learn when you are excited to teach. Check out the Top Ten Reasons to Code.)
- How will you assess your students? (This PDF details some research on assessing computational thinking.)
3. Get Support
Just because anyone can learn to code online doesn’t mean that’s the best way to do it. Code.org’s research found that “students who are learning with the support of their teacher in a classroom setting complete courses more than those learning on their own” (Teachers Matter). We all know that for teachers to be successful, we need support. So rally the troops!
- Find a champion for your coding crusade. The higher level the champion is, the easier it will be for you to gain access to resources and spread the word about your 21st-century class.
- Get the community involved. Host an Hour of Codecommunity event. Last year, the Avondale Elementary School District held an Hour of Code event where the students taught their parents how to program.
- Build your PLN. Follow people on your favorite social network and ask for help. Some great hashtags are#CSK8, #KidsCanCode, and #AllKidsCode.
- Present to your governing board. Show them how your curriculum aligns to CCSS and builds 21st-century skills.
Jump Into 21st-Century Learning!
If you’ve already had successful experiences coding in your class, share them in the comments section of this post or on your PLN. If not, you may be asking the following questions:
- Will you know the answer to every question that your students will have?
- Will you feel well rested, prepared, and in control at all times?
- Will every class run without a hitch?
Answers: 1) No. 2) You wish. 3) In your dreams!
Will it be worth it? You better believe it! Now go make it happen!
15+ Ways of Teaching Every Student to Code
(Even Without a Computer)
…While the Hour of Code is in December, Code.org hassuggested resources for educators, unplugged lessons (those not requiring computers), and tutorials to help you teach computer science to kids of all ages any time of the year….
- Scratch is a programming game that can be downloaded or used on the Web and is supported by MIT. They’ve got a powerful Hour of Code tutorial where students can program a holiday card in their web browser.
- Lightbot has a version on just about any platform and even has an online one-hour version. This puzzle game has a free version which lasts an hour but sells full versions on iTunes and Google Play. It teaches planning, testing, debugging, procedures, and loops.
- Kodu is another programming tool that can be easily used on a PC or XBOX to create a simple game. There’s also a math curriculum. This is one method that Pat Yongpradit, Code.org’s Director of Education, used in his computer science classroom. (I’ve used it as well.)
- Gamestar Mechanic offers a free version that you might want to use for your hour, but if you fall in love with it, the educational package allows teachers to track student progress, among other features. The company supports educators, and there’s also an Edmodo community that shares lesson plans and ideas for the tool, along withvideos and a must-see teacher’s guide.
- GameMaker is an option if you want to make games that can be played in any web browser. The resources aren’t as comprehensive and the community isn’t vibrant, but this one has been around for a while and might be fun for a more tech-savvy teacher.
- My Robot Friend is a highly-rated app according toCommon Sense Media. It costs $3.99, but no in-app purchases are required to go to higher levels.
- SpaceChem is an interesting mix of chemistry, reading, and programming for age 12 and up. As students read the 10,000-word novelette, they have to solve puzzles by assembling molecules. SpaceChem created a helpful guide for educators. This tool is available for download on Steam and installation on Windows, Mac, and Ubuntu. (Download a free demo.)
- CodeCombat is a multiplayer game that teaches coding. It’s free to play at the basic level, and students don’t have to sign up. This has the advantage that teachers don’t have to know computer science to empower learning in this programming. It’s recommended for age 9 and up. See theteacher guide for the information and standards covered in this game.
- Minecraft.edu is an option that lets you install and use Minecraft in the classroom. While this does require some purchase and setup, Minecraft seems to be gaining in popularity among educators as an in-house, 3D world-programming environment that kids love. Minecraft.edu has a Google group and best practices wiki. (My son took a course at Youth Digital that taught him Java to mod Minecraft — while pricey, it was a great course.)
- Do you want a board game for older children? Code Monkey Island is designed for children age 9 and up. This is a great addition to your game corner.
Tutorials Point originated from the idea that there exists a class of readers who respond better to online content and prefer to learn new skills at their own pace from the comforts of their drawing rooms. The journey commenced with a single tutorial on HTML in 2006 and elated by the response it generated, we worked our way to adding fresh tutorials to our repository which now proudly flaunts a wealth of tutorials and allied articles on topics ranging from programming languages to web designing to academics and much more.
Programming Lego NXT robots
On Physics Central Tamela Maciel writes:
That smartphone you carry around in your pocket all day is a pretty versatile lab assistant. It is packed with internal sensors that measure everything from acceleration to sound volume to magnetic field strength. But I’ll wager most people don’t realize what their phones can actually do. Apps like SensorLog (iOS) or AndroSensor (Android) display and record raw data from the phone’s movement, any background noises, and even the number of satellites in the neighborhood. Watching this data stream across my screen, I’m reminded just how powerful a computer my phone really is. Wrapped into one, the smartphone is an accelerometer, compass, microphone, magnetometer, photon detector, and a gyroscope. Many phones can even measure things like temperature and air pressure.
Useful for STEM education, academia, and industry, this app uses device sensor inputs to collect, record, and export data in comma separated value (csv) format through a shareable .csv file. Data can be plotted against elapsed time on a graph or displayed digitally. Users can export the data for further analysis in a spreadsheet or plotting tool. See http://www.vieyrasoftware.net for a variety of usage ideas
(1) G-Force Meter – ratio of Fn/Fg (x, y, z and/or total)
(2) Linear Accelerometer – acceleration (x, y, and/or z)
(3) Gyroscope – radial velocity (x, y, and/or z)
(4) Barometer – atmospheric pressure
(5) Roller Coaster – G-Force Meter, Linear Accelerometer, Gyroscope, and Barometer
(6) Hygrometer – relative humidity
(7) Thermometer – temperature
(8) Proximeter – periodic motion and timer (timer and pendulum modes)
(9) Ruler – distance between two points
(10) Magnetometer – magnetic field intensity (x, y, z and/or total)
(11) Compass – magnetic field direction and bubble level
(12) GPS – latitude, longitude, altitude, speed, direction, number of satellites
(13) Inclinometer – azimuth, roll, pitch
(14) Light Meter – light intensity
(15) Sound Meter – sound intensity
(16) Tone Detector – frequency and musical tone
(17) Oscilloscope – wave shape and relative amplitude
PDF Labs to use with smartphone apps
Simple Harmonic Motion, and measuring Period
Smartphone Physics in the Park
Here’s a simple physics experiment you can do at your local park.
By swinging on a swing and collecting a bit of data, you can measure the length of the swing – without ever pulling out a ruler.
1. To get started, download the free SPARKvue app (or another data logger app like SensorLog or AndroSensor). Open it up and have a play.
By clicking on the measurement you want to track and then clicking on ‘Show’, you will see an graph window open with a green play button in the corner.
Click the play button and the phone will start tracking acceleration over time.
To stop recording, click the play button again.
Save your data using the share icon above the graph.
2. Find a swing.
3. Fix your phone to the swing chain with tape – or hold it really still against your chest in portrait orientation with the screen facing your body.
Since I was a bit lazy, I opted for the latter option but this makes the final data a bit messier with all the inevitable extra movement.
You want portrait orientation in order to measure the acceleration along the direction of the swing chains.
This will tell us how the centripetal acceleration from the tension in the chains changes as you swing.
4. Start swinging and recording the Y-axis acceleration, without moving your legs or twisting your body. Collect data for about 20 seconds.
5. Stop recording and have a look at your lovely sinusoidal graph.
You could try to do the next step directly from this graph.
I wanted a bigger plot, so I saved the raw data and copied it into Excel.
Here are the first 20 seconds of my swing.
Plotting the centripetal (Y-axis) acceleration against time.
You can immediately see the sine wave pattern of the swing,
and the fact that the height of the peaks is decreasing over time.
This is because all pendulums have a bit of friction and gradually come to a halt.
Keep in mind that this plot shows the change in acceleration, not velocity or position.
|Acceleration of a swing, as measured along the chain of a swing. Data collected with SPARKvue and graphed in Excel. Credit: author, Tamela Maciel|
6. Measure the period of the swing from the graph.
|Direction of total velocity and acceleration for a simple pendulum.
Credit: Ruryk via Wikimedia Commons
To make sense of the peaks and troughs:
think about the point mid-swing when your speed is highest.
This is when you’re closest to the ground, zooming through the swing’s resting point.
It is at this point that the force or tension along the swing chain is highest, corresponding to a maximum peak on the graph.
The minimum peaks correspond to when you are at the highest point in the swing,
and you briefly come to a stop before zooming back down the other way.
Check out The Physics Classroom site for some handy diagrams of pendulum acceleration parallel and perpendicular to the string.
Once we know what the peaks represent,
we can see that the time between two peaks is half a cycle (period).
Therefore the time between every other peak is one period.
For slightly more accuracy, I counted out the time between 5 periods (shown on the graph)
and then divided by five to get an average period of 2.65 seconds per swing.
A simple pendulum has a period that depends only on its length, l,
and the constant acceleration due to gravity, g:
I measured T = 2.65 s and know that g = 9.8 m/s/s,
so I can solve for l, the length of the swing.
I get l = 1.74 meters or 5.7 feet.
This is a reasonable value, based on my local swing set, but of course I could always double check with a ruler.
Now a few caveats: my swing and my body are not a simple pendulum, which assumes a point mass on the end of a weightless string.
I have legs and arms that stick out away from my center of mass, and the chains of the swing definitely do have mass.
So this simple period equation is not quite correct for the swing (instead I should think about the physics of the physical pendulum).
But as a first approximation, the period equation gives a pretty reasonable answer.
By the way , here are comments on the above graph:
Claim: “Your graph is wrong. You write at the peaks, where the acceleration is highest, that the velocity is highest and the mid-swing-point. That is wrong. There is also a turning point with lowest velocity. The highest velocity and the mid-swing-point is where the acceleration is 0.”
Remember, the phone is only recording the y-component of the total acceleration. At the end points the where the acceleration, a, is at maximum, but is at right angles to the chains so the y-component is zero.
This coincides with the velocity reaching zero as well.
At the mid-point where the velocity reaches maximum, the x-component of the acceleration is zero and the y-component reaches its maximum.
There is no point where the total acceleration reaches zero, only the x-component.
My phone was measuring only the y-component of the acceleration, which from the way I held it, was only along the direction of the chains.
The maximum acceleration or force along the chains happens at the mid-point of the swing.
The minimum acceleration along the chains happens at the turning point.
So the graph is correct for the y-component acceleration.
But it would be interesting to repeat the experiment measuring the acceleration in the x-component, where the graph would look somewhat different.
Other experiments to explore
Morelessons from Vieyra software
Smartphones in science teaching
Mobile sensor apps for learning physics: A Google Plus community
Article: Turn Your Smartphone into a Science Laboratory
Using smartphone apps to take physics day to the next level
Placing the smartphone onto a record, playing on a turntable
To study angular motion
Smartphone app contest
Many more ideas https://mobilescience.wikispaces.com/Ideas
Physics Toolbox Apps by Vieyra Software http://www.vieyrasoftware.net/browse-lessons
Belmont University Summer Science Camp
Physics with Phones, Dr. Scott Hawley http://hedges.belmont.edu/~shawley/PhonePhysics.pdf
Familiarizing Students with the Basics of a Smartphone’s Internal Sensors
Colleen Lanz Countryman, Phys. Teach. 52, 557 (2014)
Full text of article, in PDF format
Music to study science by
The Boston Symphony Orchestra as caught in its incomparable native habitat, Symphony Hall.(c) Stu Rosner
Education in music and poetry is most important … because rhythm and harmony permeate the inner part of the soul more than anything else, affecting it most strongly and bringing it grace, so that is someone is properly educated in music and poetry, it makes him graceful. But if not, then the opposite. And because anyone who has been properly educated in music and poetry will sense it acutely when something has been omitted from a thing and when it hasn’t been finely crafted or finely made by nature.”
– Plato, The Republic III 401d-e.
Ludwig van Beethoven, Symphony No. 9 in D Minor 4th Movement, “Ode To Joy”, English version, “Joyful, Joyful, We Adore Thee”, at Royal Albert Hall, London, England
Ode to Joy – Flash Mob Started by One Little Girl: To pay homage to the town they love and to celebrate their 130 anniversary Sabadell Bank in Spain delighted the townspeople with an incredible symphony flash mob. Watch as they play Ludwig van Beethoven’s Ninth Symphony and sang Ode to Joy, filling up the town with joy and beautiful music!
Ludwig van Beethoven, Symphony No. 9 in D Minor 4th Movement, “Ode To Joy” – Complete w/ Words and Translation – Long
Georges Bizet – Carmen – Overture
Frédéric Chopin, Minute Waltz, 1847
Full name: Waltz in D-flat major, Op. 64, No. 1, Valse du petit chien (French for Waltz of the little dog)
Franz Liszt, Hungarian Rhapsody No.2 , 1847
W. A. Mozart, Symphony No. 40, 1st Movement “Allegro”
W. A. Mozart, Rondo Alla Turca. Known formally as Piano Sonata No. 11 in A Major
Johann Pachelbel (1653-1706)
Canon in D. Full name – Canon and Gigue for 3 violins and basso continuo
Boston Pops Orchestra, Conductor John Williams.
Gioachino Rossini, The Barber of Seville (1816)
(link to be added)
Gioachino Rossini, LARGO AL FACTOTUM from The Barber of Seville
Gioachino Rossini, The William Tell Overture (1829)
Bedřich Smetana: Dance of the Comedians (1866) NOVA filharmonija
dirigent: Simon Perčič, Novoletni capriccio, Slovenska filharmonija, Ljubljana, 23.12.2013
The Blue Danube, Johann Strauss II (1825 – 1899)
André Rieu & his Johann Strauss Orchestra playing “The Beautiful Blue Danube” (An der schönen blauen Donau)
Pyotr Ilyich Tchaikovsky, The Nutcracker Suite, 1892
Antonio Vivaldi – Four Seasons. 1723
Budapest Strings, Bela Banfalvi, Conductor
Richard Wagner, Overture from The Flying Dutchman (German: Der fliegende Holländer) , (1843)
Richard Wagner, Pilgrim’s Chorus, from Tannhäuser
Tannhäuser and the Minstrel’s Contest at the Wartburg”) 1845
Richard Wagner, “Ride of the Valkyries”
Act 3 of Die Walküre, the second of the four operas by Richard Wagner that constitute Der Ring des Nibelungen (The Ring of the Nibelung)
Jan Peerce (Joshua Perelmuth) sings The Kol Nidre (Hebrew)
French National Anthem – “La Marseillaise” (French, with English translation)
The Arts Disciplines: Music
5.1 Perceive, describe, and respond to basic elements of music, including beat, tempo, rhythm, meter, pitch, melody, texture, dynamics, harmony, and form
5.2 Listen to and describe aural examples of music of various styles, genres, cultural and historical periods, identifying expressive qualities, instrumentation, and cultural and/or geographic context
Arts in world history: The Age of Revolutionary Change (C. 1700 TO 1914)
Europe: The Classical Style (1750–1825)
Developing forms of music: Sonata, concerto, symphony, instrumental chamber music. Sonata allegro form used extensively in large forms. Emergence of the fortepiano over other keyboard instruments.
Composers: Wolfgang Amadeus Mozart, Ludwig van Beethoven, Franz Joseph Haydn, C.P.E. Bach, J.C. Bach, Carl Maria von Weber, Christoph Willibald Gluck, Luigi Cherubini
The Romanticists (1800–1900) Developing forms of music: Great expansion of all major forms of music, especially the symphony and opera, as well as long solo works. Prominence of piano in chamber music. Descriptive program music. Emergence of
nationalism in composition, use of folk music.
Composers: Hector Berlioz, Franz Schubert, Felix Mendelssohn, Frédéric Chopin, Robert Schumann, Franz Liszt, Richard Wagner, Giuseppe Verdi, César Franck, Anton Bruckner, Johannes Brahms, Georges Bizet, Modest Mussorgsky, Peter Ilyich Tchaikovsky, Antonin Dvorák, Edvard Grieg, Nikolai Rimsky-Korsakov, Giacomo Puccini, Gustav Mahler, Jan Sibelius, Bedrich Smetana.
We can’t always trust what the media reports. This week is a great example: Major newspapers like The Telegraph (UK) and The Guardian (USA) print misleading headlines about science research, in this case, headlines that are totally wrong – almost the opposite of what the original research shows.
How does this happen? In ‘Motherless babies!’ How to create a tabloid science headline in five easy steps, Gretchen Vogel explains how a simplification led to an over-simplification, which led to journalists completely misrepresenting the actual science. None of this is happening on purpose, and there’s no conspiracy. But this kind of thing happens all the time, so we must learn some science ourselves, and learn to read critically.
Gretchen Vogel writes:
No, scientists have not figured out how to make “motherless babies,” nor have they gotten any closer to making an embryo without using an egg cell. A paper published yesterday in Nature Communications sparked a flurry of headlines about futuristic ways to get around the basic formula of “sperm plus egg equals embryo.”
Mice produced by mitotic reprogramming of sperm injected into haploid parthenogenotes
Toru Suzuki, Maki Asami, Martin Hoffmann, Xin Lu, Miodrag Gužvić, Christoph A. Klein & Anthony C. F. Perry. Nature Communications 7, Article number: 12676 (2016)
Many stories claimed researchers had moved closer to using a skin cell, for example, instead of an egg cell, to make a baby. That, they said, could make it possible for a gay couple to have a baby by fusing sperm from one man with the skin cell of another.
But those headlines and stories frequently left out a crucial detail: The researchers, led by Tony Perry, an embryologist at the University of Bath in the United Kingdom, most definitely needed egg cells—also called oocytes—to make the mouse pups they described.
The egg cells they experimented on were past the typical “use by” date, in that they had been chemically prompted to start dividing. (Usually it is fertilization by sperm that provides that signal.) That meant that they had started to grow into parthenogenotes, an unusual type of early embryo. The cells in parthenogenotes contain only half as many chromosomes as usual—precisely because they start out as an egg that has not been fertilized.
When scientists took one cell from a two-cell parthenogenote—roughly half a day after they had tricked the egg to start cell division—and then injected a sperm cell, the combination sometimes went on to develop into a mouse pup. Roughly a quarter of the parthenogenote cell plus sperm cell combinations produced pups, the authors report.
That is mildly interesting to people who study the nitty-gritty of cell division and fertilization—hence the widely reported comment that the work was a “technical tour de force,” obtained by the Science Media Centre (SMC) from Robin Lovell-Badge of the Francis Crick Institute in London and distributed to journalists (see below).
But it has nothing to do with the idea of making an embryo without using an egg cell. As most introductory biology textbooks explain, what makes sperm and egg cells able to merge and make a new organism is that they each contain only half as many chromosomes as other cell types. The technical term for this is a haploid cell. (Cells with the usual number of chromosomes are diploid.) Skin cells are definitely not haploid, and no one has come close to figuring out how to make them so.
In addition, the egg cell contains powerful, as yet unknown factors that enable it to direct the first steps of embryo development. Those factors are what drive somatic cell nuclear transfer—better known as cloning—the process that famously led to the creation of Dolly the sheep from a (diploid) mammary gland cell. The new paper shows that enough of the egg cell magic is still present even after it has been tricked into dividing from one cell into two. But it does not reveal what any of those powerful factors are, nor does it suggest how they might be inserted into a skin cell.
For better or worse, egg cells are still irreplaceable.
So, without further ado, the recipe for transforming a modest developmental biology paper into a blockbuster story, as it played out yesterday in the media:
- Take one jargon-filled paper title: “Mice produced by mitotic reprogramming of sperm injected into haploid parthenogenotes“
- Distill its research into more accessible language. Text of Nature Communications press release: Mouse sperm injected into a modified, inactive embryo can generate healthy offspring, shows a paper in Nature Communications. And add a lively headline: “Mouse sperm generate viable offspring without fertilization in an egg“
- Enlist an organization to invite London writers to a press briefing with paper’s authors.
Headline of Science Media Centre press release: “Making embryos from a non-egg cell“
- Have same group distribute a laudatory quote from well-known and respected scientist:
“[It’s] a technical tour de force.”
- Bake for 24 hours and present without additional reporting. Headline in The Telegraph:“Motherless babies possible as scientists create live offspring without need for female egg,” and in The Guardian: “Skin cells might be used instead of eggs to make embryos, scientists say.”
Such headlines appear to have the London-based SMC second-guessing its decision to hold a press briefing on the work. Fiona Fox, SMC director, sent Science the following statement when asked whether it contributed to the hype:
“The SMC is reflecting on the media coverage generated by this new study, which was very speculative, resulting in the kind of headlines we are wary of. I think this was a classic case of the tension between a study that is scientifically significant and interesting to researchers in the field, but far too basic and preliminary for news journalists who need to draw real world implications to engage their readers. Having struggled to explain the very complex scientific significance of the specific advance made by his team, Dr. Perry was happy to help the journalists in the room to speculate about the future implications of creating an embryo without an egg in an effort to trace those possible developments back to the specifics of his team’s work. Despite stressing no fewer than five times that the future scenarios were ‘speculative and fanciful’ it was these sci fi possibilities that seized the imagination of the journalists and generated excitable headlines.
There were two other unusual factors in this story—the extremely complex and technical nature of the science, which even experienced science press officers and journalists struggled to grasp, and the fact that despite several attempts the SMC was unable to find any experts in the field with the time needed to study the paper and provide the kind of measured context that third party experts can usefully add to the authors’ interpretation. Running a press briefing on discoveries in basic science always poses a dilemma. Is it better to leave alone basic science like this; or to present it as accurately as possible to journalists, even if it ends up generating speculation on its future application? I’m not sure there’s an easy answer to that.”
Lovell-Badge says he, too, was dismayed by the press reaction. “I thought Tony’s paper was well-done technically,” he tells Science. But “it doesn’t get us closer to making haploid cells out of diploid ones … [and] it does not say that oocytes are not needed.”
With reporting by Science News Staff.
History of robotics and coding
200 BCE – The Antikythera mechanism – analogue computer and orrery used to predict astronomical positions and eclipses for calendrical and astrological purposes
Orrery is a mechanical model of the solar system that illustrates or predicts the relative positions and motions of the planets and moons, usually according to the heliocentric model.
1348, Giovanni Dondi (Italy) built the first known clock driven mechanism which displays the ecliptical position of Moon, Sun, Mercury, Venus, Mars, Jupiter and Saturn
1822- Charles Babbage’s mechanical difference engine: automatic mechanical calculator designed to tabulate polynomial functions.
1837 – Charles Babbages Analytical Engine was a proposed mechanical general-purpose computer
Augusta Ada King-Noel, Countess of Lovelace (née Byron; 1815 – 1852) English mathematician and writer, known for her work on Charles Babbage’s early mechanical general-purpose computer, the Analytical Engine. Her notes on the engine include first algorithm intended to be carried out by a machine. The first computer programmer
DaVinci’s prototype robot car
How intelligent are people? What does it even mean to be conscious? Aware of one’s own self?
Could AIs (artificial intelligences) be more intelligent than people?
And is “more” or “less” the only way to compare intelligent? Different minds may not simply be smarter than others, they may think differently. Instead of having a 1-D axis for intelligence (e.g. an IQ scale), we may need 2 or 3 dimensions to map out all possible types of minds.
For an example of non-human intelligences here on Earth, see consciousness in Human and non-Human Animals.
Here’s a great comparison:
What in god’s name was this octopus trying to do? Maybe that’s the wrong question. There’s no question that octopi are smart — they can puzzle their way through surprisingly complex tasks — but they’re also not a lot like humans. There’s only a limited extent that we can empathize with animals — and there’s a good chance that we’ll get it wrong. (c.f. http://organizations.utep.edu/portals/1475/nagel_bat.pdf)
Octopi, though. Octopi are particularly difficult, and I don’t know if “volition” is really the right model to describe what this animal is trying to do.
Most of an octopus’ neurons are in its arms. The rest are in a donut-shaped brain that surrounds its digestive tract. Vision and hearing are handled centrally, but proprioception, smell, touch, and taste are mostly delegated to the nerve cords in the arms.
Which means that, subjectively, an octopus is probably something like an unruly parliament of snakes ruled by a dog.
If you’ve ever gotten a chance to interact with an octopus in person, you’ll find that it really doesn’t have much control over the details of what its tentacles do. Run your finger over the sensory surface, and its suckers will cup your fingers and the end will curl around it. Only afterward — when the octopus actually looks at what you’re doing — does the octopus seem to get a grip on what its tentacle is gripping.
This octopus is crawling out of its tank. But it probably doesn’t have a great idea about where the tips of its tentacles are, and — because it can’t see what its arms are doing — probably doesn’t yet know that it’s trying to make a break for freedom.
The Wechsler IQ tests are the most frequently used individual IQ tests; they are the “gold standard” in IQ testing. Like all current IQ tests, it reports a “deviation IQ” as the standard score for the full-scale IQ, with the norming sample median raw score defined as IQ 100 and a score one standard deviation higher defined as IQ 115 (and one deviation lower defined as IQ 85).
|IQ Range (“deviation IQ”)||IQ Classification|
|130 and above||Very Superior|
|69 and below||Extremely Low|
The Universe of Minds, Roman V. Yampolskiy
What is a mind? No universal definition exists. Solipsism notwithstanding, humans are said to have a mind. Higher order animals are believed to have one as well and maybe lower level animals and plants or even all life forms. We believe that an artificially intelligent agent such as a robot or a program running on a computer will constitute a mind…. we will limit our analysis to those minds which can actively interact with their environment and other minds.
…Overall the set of human minds (about 7 billion of them currently available and about 100 billion ever existed) is very homogeneous both in terms of hardware (embodiment in a human body) and software (brain design and knowledge). In fact the small differences between human minds are trivial in the context of the full infinite spectrum of possible mind designs. Human minds represent only a small constant size subset of the great mind landscape. Same could be said about the sets of other earthly minds such as dog minds, or bug minds or male minds or in general the set of all animal minds…
Yudkowsky describes the map of mind design space as follows: “In one corner, a tiny little circle contains all humans; within a larger tiny circle containing all biological life; and all the rest of the huge map is the space of minds-in-general. The entire map floats in a still vaster space, the space of optimization processes. Natural selection creates complex functional machinery without mindfulness; evolution lies inside the space of optimization processes but outside the circle of minds”
Figure 1 illustrates one possible mapping inspired by this description.
Yudkowsky describes the map of mind design space as follows: “In one corner, a tiny little circle contains all humans; within a larger tiny circle containing all biological life; and all the rest of the huge map is the space of minds-in-general. The entire map floats in a still vaster space, the space of optimization processes” (Yudkowsky 2008, 311).
Ivan Havel writes:
All conceivable cases of intelligence (of people, machines, whatever) are represented by points in a certain abstract multidimensional “super space” that I will call the intelligence space (shortly IS).
Imagine that a specific coordinate axis in IS is assigned to any conceivable particular ability, whether human, machine, shared, or unknown (all axes having one common origin). If the ability is measurable the assigned axis is endowed with a corresponding scale. Hypothetically, we can also assign scalar axes to abilities, for which only relations like “weaker-stronger,” “better-worse,” “less-more” etc. are meaningful; finally, abilities that may be only present or absent may be assigned with “axes” of two (logical) values (yes-no).
Let us assume that all coordinate axes are oriented in such a way that greater distance from the common origin always corresponds to larger extent, higher grade, or at least to the presence of the corresponding ability. … (Havel 2013, 13)
Human minds – that’s what we humans currently have, from a day old baby, to a child in 3rd grade, to an adult businesswoman, to the greatest geniuses the world has ever seen, like Albert Einstein and Isaac Newton. We’re all represented in the pink dot, in the image above.
Transhuman minds are the minds of humans who have chosen to augment and extent their intellectual powers and physical bodies through genetic engineering, cybernetics, networking their brains to computers, replacing body parts.
Transhumanism is”the intellectual and cultural movement that affirms the possibility and desirability of fundamentally improving the human condition through applied reason, especially by using technology to eliminate aging and greatly enhance human intellectual, physical, and psychological capacities” – Nick Bostrum, 1999.
Posthuman minds would go far beyond this; if humans continue to push their biology and minds past the transhuman state, the result would be a being that no longer looks or thinks like a human being.
Freepy AIs are any type of artificial intelligence that human beings might be able to make; although they may produce results we can understand, we can’t understand the way that they think. They are not only smarter than us, they think differently than we do.
Bipping AI’s are a kind of artificial intelligence so advanced that humans couldn’t even possibly design them. They might be designed by other AIs, or by transhumans, or posthumans. They are amazingly intelligent, but utterly nonhuman. It might not even be possible to have a conversation with them, since their view of reality and their way of thinking about the world is so different from our own.
Gloopy AI’s Bipping AI’s are a kind of artificial intelligence so advanced that humans couldn’t even possibly design them, but not necessarily smarter than us. They would have a capacity to think, but perhaps at a lesser organized level. It might not even be possible to have a conversation with them, since their view of reality and their way of thinking about the world is so different from our own.