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A.I. HEROES: Learn STEM and get inspired by your own scientific heroes!
Summary
Have you ever dreamed of having Einstein, Marie Curie, Galileo, or Dorothy Vaughan as your teachers in your science classes at school? Well, now thanks to machine learning, chatbox, text-to-speech, and A.I. synthetic media technologies working together all this can be possible with "A.I. HEROES", a cutting-edge learning platform where you can learn and be inspired by your “scientific heroes" to make history. You can learn about their own theories, contrast the resources they had at their time with the ones you have available nowadays thanks to NASA, and maybe even joke and have fun with them about their own life stories. Let these heroes inspire you to become one yourself in the future.
How We Addressed This Challenge
A.I. Heroes team members: Jonathan Feller (Brazil), Yash Gadhade (India), Andrea Ybañez Esquerre (Peru), Raquel Sánchez Mejía (Peru) and Marco Carrasco (Peru). Very special thanks to: Umar, Triandy Tressa and Diego Ruiz.
A.I. Heroes Video, to watch it please click here: https://youtu.be/izDxpfOIF6M
Video: Made for this project.
OUR TARGET AUDIENCE
Our project is aimed at children and teenagers from all over the world. To those who may think science as something boring, to those who have little access to science resources, and to those minorities who are underrepresented. What is happening? STEM careers are very attractive to everyone and have broad global support (BEIS Research, 2020). But, when a child is taught about physics, mathematics, astronomy, and other related sciences, it can be difficult to understand and thus some mistakenly start seeing them as boring, especially if it is accompanied by little interactive teaching. This is how, from a very young age, children can lose interest in them.
Image: Made for this project.
Gender and racial inequality in the world of STEM persists. For instance, STEM-related careers are perceived to be predominantly male, which could limit women and girls in choosing these types of careers (Makarova, 2019). How is it reflected in the facts? Since 1903, when Marie Curie won the Nobel Prize in Physics, only 17 women have won a Nobel Prize in physics, chemistry, or medicine, compared to 572 men (UNESCO, 2017). Globally, less than 30% of all researchers are women (UIS, 2019). It's no surprise then that when you ask a child to “draw a scientist”, most of them end up drawing white men in lab coats and instruments that reflect a chemistry lab (Miller et al., 2018; Thomson, 2019). A broad stereotype that does not show cultural diversity in science or in STEM-related careers, probably because it is not seen in the media or in its context, although there are large contributions by black people, of another race or nationality.
Image: Drawing of a “white man” by a girl when asked to “draw a scientist”.
Despite notable achievements in STEM by minority groups, more investment in them remains to be done. Children in developing countries may have a dream of being an astronaut but this would remain only a dream because they may not have the necessary understanding of the basic concepts of physics and mathematics, neither the local role models to be inspired to accomplish so. How frustrating for a child this can be! For instance, in the last PISA test, it was evidenced that countries such as the Dominican Republic, the Philippines and Kosovo had one of the lowest scores in understanding about Science and Mathematics, compared to countries such as China and Finland. A good education that defends equal rights, that is, an inclusive and quality education will allow to take root in the minds of the smallest in these types of conditions, which will allow them to recover their curiosity and emotion of seeing it possible to have such a career and become the next brilliant minds or "heroes" of the future.
OUR MISSION AND KEY MESSAGE
Faced with a context of unequal opportunities and wasting of the knowledge provided, we were motivated to create A.I. Heroes. Our heroes will be able to immerse children and teenagers in the world of science, making it closer and more fun. In addition, they can become role models for children, becoming guides for future plans that they can build from a young age. Moreover, the use of recognizable and fun characters with nice facial expressions will help to provide a sort of companionship feeling, something especially valuable during stressful times such as current pandemic.
Image: Made for this project.
Our heroes as role models can have more impact if they share characteristics with you. For example, what better way to change stereotypes for a girl than to interact with a female scientist like Marie Curie, or for a girl in India to talk to an Indian astronaut from his own country instead of a foreigner. They can inspire change. Indeed, for instance, 51% of girls with a role model can more easily visualize themselves working in a STEM career (Microsoft, 2018) .Thus, in absence of physical role models, our heroes (tailored to cover gender diversity and most geographical locations) could also inspire and motivate many children and teenagers to pursue their dreams in STEM careers, and why not, maybe working in the future NASA.
We also want to reach out to countries where STEM careers don't have much of a presence, especially in low-income countries. It is precisely these countries that most need STEM to facilitate economic development and international competitiveness. Incorporating people into STEM has brought great benefits as in Rwanda where engineering education has provided better solutions to problems in local development (K4D, 2018).
That is why we also incorporated in our first set of characters some heroes from different countries, such as Kalpana Chawla, thus generating greater identification in every way. These types of heroes, in addition to explaining in an interactive way about science and technology, can motivate children to go beyond the adverse conditions that many developing countries can find themselves struggling at the moment. Dreaming high and having perseverance will be a great key to achieving your goals. Finally, one final focus is on black people who have long been discriminated against and their achievements have often been made invisible.
Image: “Representation matters”. Lily as Mae Jemison. Bushelle & Harper (2015).
OUR FIRST SET OF A.I. HEROES
Here we provide a list of 10 identified scientific heroes and heroines that are part of our first version. As a way to inspire all children and teenagers from all around the world, this selection aimed to be balanced in matters of their scientific impact, inspirational power, gender diversity, and geographical location. A next version of our project may also include a second set of even more diverse A.I. Heroes.
Image: Our group A.I. Heroes designs and info-boxes made for this project. Scientist real photos and pictures are used here under fair use due to be for educational and non-profit purposes.
Image: For instance, Dorothy Vaughan and Stephen Hawking could be role models and inspiration for girls from Africa and kids with special needs.
APPLYING MULTIMEDIA LEARNING PRINCIPLES
Our little heroes can have a greater presence in the classroom supporting the teaching of teachers in STEM or in distance education that has a lot to improve in current times. The fact that our characters are interactive is one of their great strengths to provide better learning for children. In fact, research confirms that people learn more with words in conjunction with multimedia animations, rather than just words. Based on the book "Applying Science of Learning in Education", we are guided by the following basic principles to provide an effective design in multimedia instruction (Mayer, 2014):
- The Temporal Contiguity Principle: People learn more deeply when narration and graphics are presented simultaneously rather than in succession. Our mascot will explain his theories by showing images or videos simultaneously.
- The Modality Principle: Pronouncing printed words when teaching allows people to learn more quickly. When our pet pronounces the words that appear in the chat in response to the question asked by the child, they will be able to download the processing of their visual channel in the verbal channel and they will have greater visual capacity for our animations.
- The Personalization Principle: We use a conversational language with the characters that allows us to generate a greater sense of social presence in the student, in this way the children will make an effort to understand more what the instructor says (e.g. say “our universe” instead of "the universe").
- The Voice Principle: Another way to generate social presence is the human voice, this is better received than the machine voice in the learning process. Whenever possible, each character's voice will have its original voice, otherwise we will be recording our own voices or perhaps, in the near future, other people in the field of education.
- The Embodiment Principle: Lastly, human-like action such as facial expressions and movements are also powerful tools for better learning. All this connects with the social presence and our characters have it.
How We Developed This Project
Even though we were a team working across continents, in different time zones, and with different languages, we still overcame all these difficulties and reached a feasible project that we hope could have a significant impact on education at the global level. Now we will show you what we have achieved in this limited time span. We have come up with a presentation version of our real idea on this link: https://ai-heroes.web.app. In this we have simply made a markup to demonstrate our core idea of using synthetic media to interact with students. As for now we made our Frontend using React and our Backend using node.js. Further resources we use for this include Google Firebase and https://github.com/alievk/avatarify. Overall, our team has represented our project through the following flowchart.
Image: Made for this project.
STEP 1: MACHINE LEARNING AND CHATBOX
Our project aims to nurture each scientist figure with the information of their own scientific theories, discoveries, and life stories. This training data will allow each character to answer some basic questions regarding their own field towards children. Two branches of the project exist from this: (a) The first one, achievable at this stage will imply the real teacher with knowledge on one precise of these historical figures to use A.I. synthetic media technology to appear and look as the specific figure. (b) The second one, still a work in progress but still achievable in some weeks due the ML necessary time to process all input will give each scientific figure a higher degree of autonomy. Overall, we could use any chatbot technology for this, for instance https://cloud.google.com/dialogflow is a good choice.
STEP 2: TEXT-TO-SPEECH
The final version of the platform will make use of a text-to-speech (TTS) system to convert normal language text into speech. As these systems are getting better each day, even though our first demo will be in English, we have explored further possibilities to reach the same objective with languages such as Chinese, Hindi, Spanish, Portuguese, among others. The voice could be synthesized using a voice cloning deep learning technique, any character for which we can get a clear voice sample, we could clone. See for instance https://github.com/CorentinJ/Real-Time-Voice-Cloning
STEP 3: A.I. SYNTHETIC MEDIA AND BEYOND (HOLOGRAMS)
The current version uses A.I. synthetic media technology to allow the control of each scientist's real picture. This technology has been previously used for bad purposes in other contexts (such as to make and spread fake news) and thus called “deepfake”. However, we proposed here a good use of it for education goals. To animate each of our characters we could make a good use of this deepfake, something that will indeed have an important impact on educational attainment and motivation as it was expressed in our flowchart and the application section above.
A future version of the project also considers the possibility to pass from Step 3 to a last one that could involve the physical personification of A.I. Heroes through holograms that could appear as scientific guides in NASA stations and scientific museums for kids visiting them.
A VERY EARLY DRAFT EXAMPLE
Image: Made for this project.
Image: Screenshot of this project.
Image: Screenshot of this project.
Image: Screenshot of this project.
Say you’re talking to Einstein, and may get some interaction like this one below. Of course, it is important to strongly remark that this is just a basic prototype, as ML will allow in more weeks to come to have more precise development on questions and answers.
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1) Student: Who are you?
A.I. Einstein: Hi! My name is Albert Einstein, I am a German born theoretical physicist, maybe mostly known because of my equation E=mc^2. What would you like to know more about?
2) Student: I would like to know more about your scientific contributions and theories.
A.I. Einstein: Well, some of my main well known contributions were the theory of relativity, the theory of stimulated emission, the law of the photoelectric effect, and my foundations of the fluctuation-dissipation theorem. I also led some theoretical framework that later my colleague Karl Schwarzschild used in 1916 to characterize the existence of black holes.
- 2.1) Student: Wow! Could you tell me more about black holes? A.I. Einstein: Sure! A black hole is a region of spacetime where gravity is so strong that nothing can escape from it. My theory of general relativity predicts that a sufficiently compact mass can deform spacetime to form a black hole. In many ways, a black hole acts like an ideal black body, as it reflects no light. You may also be interested that on 10 April 2019, the first direct image of a black hole and its vicinity was published, following observations made by the Event Horizon Telescope in 2017 of the supermassive black hole in Messier 87's galactic center.
- 2.2) Student: Wow! Could you tell me more about the theory of relativity? A.I. Einstein: Sure! The theory of relativity usually encompasses two interrelated theories I made: special relativity and general relativity. Special relativity applies to all physical phenomena in the absence of gravity. General relativity explains the law of gravitation and its relation to other forces of nature. As one practical example, relativity explains why clocks on our satellites are ahead of those on Earth by 38,000 nanoseconds. May not seem like so much, but if this time wasn’t accounted for, our GPS systems would be off by kilometers.
- 2.3) Student: Wow! Could you tell me more about the theory of stimulated emission? A.I. Einstein: Sure! I theoretically discovered stimulated emission within the framework of the old quantum theory, wherein the emission is described in terms of photons that are the quanta of the electromagnetic field. Your current laser device technology is based on this theory. Common activities you may perform like reading a barcode or using a pointer are based on my theory, but also more complex ones such as delicate surgery or industrial processes that require exact precision.
- 2.4) Student: Wow! Could you tell me more about the photoelectric effect? A.I. Einstein: Sure! The photoelectric effect is the emission of electrons when electromagnetic radiation, such as light, hits a material. Electrons emitted in this manner are called photoelectrons. The effect has found use in our electronic devices specialized for light detection and precisely timed electron emission. Without my law of the photoelectric effect, for which by the way I received the Nobel Prize in Physics in 1921, your devices that turn light into electricity, such as solar panels, would not be possible.
- 2.5) Student: Wow! Could you tell me more about the fluctuation-dissipation theorem? A.I. Einstein: Sure! Indeed, my explanation of Brownian motion was one of the main antecedents for the general fluctuation-dissipation theorem. This general theorem is a powerful tool in statistical physics for predicting the behavior of systems that obey detailed balance. Interestingly, it applies both to classical and quantum mechanical systems. Even though I developed this to explain the random movement that was observed in particles found in liquid or gas, the movements of price fluctuations seen in our stock markets are not that different. So, since 1970 when this similarity was observed, my equations have also been used on Wall Street.
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How We Used Space Agency Data in This Project
Space agency gallery pictures, videos, animations, and resources will be used to illustrate all the concepts, theories and discoveries related to each of our specific scientists. We also want to provide the opportunity to show children and teenagers the information most of these scientists had at their time and contrast it with the media resources that luckily our generation currently have thanks to Space Agencies such as NASA, CSA, CNES, JAXA, and ESA. For instance, for primary school students, Galileo himself will have the opportunity to show what he observed regarding Jupiter and its moons in 1610, and then show what he “dreamed about” to observe at his time, but that only now we can observe thanks to scientific progress (NASA Images, 2000). Another example could be for secondary school students, to which Einstein will have the opportunity to show one of his papers related to black holes and then to contrast it with what we currently know about black holes thanks to an animation provided by Space agencies (NASA Images, 2018). Further examples could be to show the rover named after Marie Curie (NASA Images, 2003) or Neil Armstrong photos when on the moon (NASA & CSA, 1969). See images and resources section below as materials that could be used for these contrasts.
Left image: Galilei, G. (1610, Jan 7 - 24). Jupiter and its moons.
Right image: NASA Images (2000). Jupiter and Ganymede. Retrieved from https://images.nasa.gov/details-PIA02862
Left image: Our group design of Marie Curie.
Right image: NASA Images (2003). Marie Curie rover during Operational Readiness Test ORT 4. Retrieved from https://images.nasa.gov/details-PIA04306
Left image: Einstein, A. (1938, Oct). On a Stationary System With Spherical Symmetry Consisting of Many Gravitating Masses. Annals of Mathematics, Second Series, Vol. 40, No. 4, pp. 922-936.
Right video: NASA Images (2018). New Simulation Sheds Light on Spiraling Supermassive Black Holes. Retrieved from https://images.nasa.gov/details-GSFC_20181002_SMBH_m13043_Simulation
Project Demo
A.I. gallery of scientist: https://drive.google.com/drive/folders/1RgmQ3Zb4DXuncu1UxL8WHZXOJ06SjQGk?usp=sharing
Solution as web platform: It is still a very initial draft beta version, due time constraint it was not possible to develop it fully. But it is feasible to achieve if provided additional time: https://ai-heroes.web.app
Share your code: It seems it was not applicable to share code for this specific challenge as the window "Share your code (if applicable)" was not activated for us, but we still share our code here: https://github.com/JonathanFeller/ai-heroes
Data & Resources
NASA AND ITS PARTNERS' RESOURCES
- NASA Images (2018). New Simulation Sheds Light on Spiraling Supermassive Black Holes [Video]. Retrieved from https://images.nasa.gov/details-GSFC_20181002_SMBH_m13043_Simulation
- NASA Images (2000). Jupiter and Ganymede [Image]. Retrieved from https://images.nasa.gov/details-PIA02862
- NASA Images (2003). Marie Curie rover during Operational Readiness Test ORT 4 [Image]. Retrieved from https://images.nasa.gov/details-PIA04306
- NASA (1969). Apollo 11: That's One Small Step for (a) Man [Audio]. Retrieved from https://www.nasa.gov/connect/sounds/index.html
- NASA & CSA (1969). First Step on the Moon - July 11, 1969 [Image]. Retrieved from https://asc-csa.gc.ca/eng/search/images/watch.asp?id=140
- NASA Goddard Media Studios (2020). Potential Giant World Circles a Tiny Star [Video]. Retrieved from https://svs.gsfc.nasa.gov/13708
- NASA Galleries (2020). Juno mission to Jupiter [Image]. Retrieved from https://www.nasa.gov/mission_pages/juno/images/index.html
- NASA Earth Observatory (2006). Photo: The Top of the Atmosphere [Image]. Retrieved from https://earthobservatory.nasa.gov/images/7373/the-top-of-the-atmosphere
- NASA Images (2020, September). Sounds from Around the Milky Way [Video]. NASA Image and Video Library. Retrieved from https://images.nasa.gov/details-sonify_galactic_all
EXTERNAL RESOURCES
- BBVA. (2018). Four contributions Einstein has made to our daily lives. Retrieved from https://www.bbva.com/en/four-contributions-einstein-made-to-our-daily-lives
- BEIS Research. (2020, July). Public Attitudes to Science 2019. (No 6). Department for Business, Energy & Industrial Strategy. Retrieved from https://www.gov.uk/government/publications/public-attitudes-to-science-2019
- Bushelle, M., & Harper, J. (2015). Lily as Mae Jemison [Photo]. My 5-Year-Old Daughter Recreates Photos Of Heroic Women To Learn History. Retrieved from https://www.boredpanda.com/recreating-historic-women-portrait-photography-heroines-marc-bushelle
- K4D. (2018, September). Benefits of STEM Education. Knowledge, evidence and learning for development. https://assets.publishing.service.gov.uk/media/5c6c0ec740f0b647abb525a7/418_Benefits_of_STEM_Education.pdf
- Mayer, R. E. (2014). Research-based principles for designing multimedia instruction. In V. A. Benassi, C. E. Overson, & C. M. Hakala (Eds.), Applying science of learning in education: Infusing psychological science into the curriculum (p. 59–70). Society for the Teaching of Psychology. Retrieved from http://hilt.harvard.edu/wp-content/uploads/2018/08/HILT_SpeakerSeries_Mayer_background_reading.pdf
- Makarova, E., Aeschlimann, B., & Herzog, W. (2019). The Gender Gap in STEM Fields: The Impact of the Gender Stereotype of Math and Science on Secondary Students’ Career Aspirations. Frontiers in Education, 4(60), 1-11. Retrieved from https://doi.org/10.3389/feduc.2019.00060
- Microsoft. (2018). How role models are changing the face of STEM in Europe. Retrieved from https://news.microsoft.com/europe/features/girls-in-stem-the-importance-of-role-models
- Miller, D. I., Nolla, K. M., Eagly, A. H., & Uttal, D. H. (2018). The Development of Children’s Gender-Science Stereotypes: A Meta-analysis of 5 Decades of U.S. Draw-A-Scientist Studies. Child Development, 89(6), 1943-1955. Retrieved from https://doi.org/10.1111/cdev.13039
- Thomson, M. M., Zakaria, Z., & Radut-Taciu, R. (2019). Perceptions of Scientists and Stereotypes through the Eyes of Young School Children. Education Research International, 2019, 1-13. Retrieved from https://doi.org/10.1155/2019/6324704
- UNESCO UIS. (2019, June). Women in Science. UNESCO UIS. Retrieved from http://uis.unesco.org/en/topic/women-science
- UNESCO. (2017). Cracking the code: Girl’s and women’s education in science, technology, engineering and mathematics (STEM). Retrieved from https://unesdoc.unesco.org/ark:/48223/pf0000253479/PDF/253479eng.pdf.multi
Image: Made for this project.
Image: Made for this project.