Designing a general education course on the societal impacts of artificial intelligence

Most colleges, including UTC, already offer an artificial intelligence course (CPSC 4440) as part of their computer science curricula. Such courses are meant to explain the technology behind these elaborate systems, but these courses often neglect extensive coverage of the real-world impacts of the technology itself. UTC also offers a course entitled “Ethical and Social Issues in Computing” that does convey the importance behind the advances of computer technology and its impacts, but this course is practically available only to computer science majors. There is no generalized and widely available course that covers the technological, economic, cultural, philosophical/theological, and ethical concerns that come with the implementation of artificial intelligence. My main endeavor in this thesis has been to review the literature of the fields involved and decide what collection of reading/film assignments best covers the necessary information when it comes to the widespread impacts of AI. I then constructed a course syllabus with clearly defined assignments and a schedule of topics. Furthermore, I discuss each decision in the construction of the syllabus and explain how and why each topic will be addressed when the course is offered in the fall semester of 2018. The final product of my research is this thesis, detailing the considerations that went into the design of the course; every anticipated discussion topic, reading, and writing assignment is laid out in detail, and the decisions for every area of the class are explained. A final syllabus for the course has been drafted as well as a completed course proposal form containing clear explanations of how this course meets the established purpose and learning outcomes of UTC’s Thought, Values, and Beliefs general education category

The Virtual University and Avatar Technology: E-learning Through Future Technology

E-learning gains increasingly importance in academic education. Beyond present distance learning technologies a new opportunity emerges by the use of advanced avatar technology. Virtual robots acting in an environment of a virtual campus offer opportunities of advanced learning experiences. Human Machine Interaction (HMI) and Artificial Intelligence (AI) can bridge time zones and ease professional constraints of mature students. Undergraduate students may use such technology to build up topics of their studies beyond taught lectures. Objectives of the paper are to research the options, extent and limitations of avatar technology for academic studies in under- and postgraduate courses and to discuss students' potential acceptance or rejection of interaction with AI. The research method is a case study based on Sir Tony Dyson's avatar technology iBot2000. Sir Tony is a worldwide acknowledged robot specialist, creator of Star Wars' R2D2, who developed in recent years the iBot2000 technology, intelligent avatars adaptable to different environments with the availability to speak up to eight different languages and capable to provide logic answers to questions asked. This technology underwent many prototypes with the latest specific goal to offer blended E-learning entering the field of the virtual 3-D university extending Web2.0 to Web3.0 (Dyson. 2009). Sir Tony included his vast experiences gained in his personal (teaching) work with children for which he received his knighthood. The data was mainly collected through interviews with Sir Tony Dyson, which helps discover the inventor’s view on why such technology is of advantage for academic studies. Based on interviews with Sir Tony, this research critically analyses the options, richness and restrictions, which avatar (iBot2000) technology may add to academic studies. The conclusion will discuss the opportunities, which avatar technology may be able to bring to learning and teaching activities, and the foreseeable limitations – the amount of resources required and the complexity to build a fully integrated virtual 3-D campus. Key Words: virtual learning, avatar technology, iBot2000, virtual universit

Unifying an Introduction to Artificial Intelligence Course through Machine Learning Laboratory Experiences

This paper presents work on a collaborative project funded by the National Science Foundation that incorporates machine learning as a unifying theme to teach fundamental concepts typically covered in the introductory Artificial Intelligence courses. The project involves the development of an adaptable framework for the presentation of core AI topics. This is accomplished through the development, implementation, and testing of a suite of adaptable, hands-on laboratory projects that can be closely integrated into the AI course. Through the design and implementation of learning systems that enhance commonly-deployed applications, our model acknowledges that intelligent systems are best taught through their application to challenging problems. The goals of the project are to (1) enhance the student learning experience in the AI course, (2) increase student interest and motivation to learn AI by providing a framework for the presentation of the major AI topics that emphasizes the strong connection between AI and computer science and engineering, and (3) highlight the bridge that machine learning provides between AI technology and modern software engineering

Enhancing Undergraduate AI Courses through Machine Learning Projects

It is generally recognized that an undergraduate introductory Artificial Intelligence course is challenging to teach. This is, in part, due to the diverse and seemingly disconnected core topics that are typically covered. The paper presents work funded by the National Science Foundation to address this problem and to enhance the student learning experience in the course. Our work involves the development of an adaptable framework for the presentation of core AI topics through a unifying theme of machine learning. A suite of hands-on semester-long projects are developed, each involving the design and implementation of a learning system that enhances a commonly-deployed application. The projects use machine learning as a unifying theme to tie together the core AI topics. In this paper, we will first provide an overview of our model and the projects being developed and will then present in some detail our experiences with one of the projects – Web User Profiling which we have used in our AI class

Different robotics platforms for different teaching needs

When facing the problem of teaching the basis of robot control programming to computer science students, apart from the syllabus of the course, some other requirements have to be taken into account. For instance, which are the most appropriate robotic platforms, and which are the best programming tools for teaching it. In this paper we describe the platforms and programming environments chosen for different senior and graduate robotic courses at Rey Juan Carlos University, focusing on the reasons under our choices. We also point out the practical assignments demanded on the courses. Finally, we will present the results along four years, the feedback from our students, and the lessons we have learne

Challenging the Computational Metaphor: Implications for How We Think

This paper explores the role of the traditional computational metaphor in our thinking as computer scientists, its influence on epistemological styles, and its implications for our understanding of cognition. It proposes to replace the conventional metaphor--a sequence of steps--with the notion of a community of interacting entities, and examines the ramifications of such a shift on these various ways in which we think

The Michigan Robotics Undergraduate Curriculum: Defining the Discipline of Robotics for Equity and Excellence

The Robotics Major at the University of Michigan was successfully launched in the 2022-23 academic year as an innovative step forward to better serve students, our communities, and our society. Building on our guiding principle of "Robotics with Respect" and our larger Robotics Pathways model, the Michigan Robotics Major was designed to define robotics as a true academic discipline with both equity and excellence as our highest priorities. Understanding that talent is equally distributed but opportunity is not, the Michigan Robotics Major has embraced an adaptable curriculum that is accessible through a diversity of student pathways and enables successful and sustained career-long participation in robotics, AI, and automation professions. The results after our planning efforts (2019-22) and first academic year (2022-23) have been highly encouraging: more than 100 students declared Robotics as their major, completion of the Robotics major by our first two graduates, soaring enrollments in our Robotics classes, thriving partnerships with Historically Black Colleges and Universities. This document provides our original curricular proposal for the Robotics Undergraduate Program at the University of Michigan, submitted to the Michigan Association of State Universities in April 2022 and approved in June 2022. The dissemination of our program design is in the spirit of continued growth for higher education towards realizing equity and excellence. The most recent version of this document is also available on Google Docs through this link: https://ocj.me/robotics_majorComment: 49 pages, approximately 25 figure

Technology assessment of advanced automation for space missions

Six general classes of technology requirements derived during the mission definition phase of the study were identified as having maximum importance and urgency, including autonomous world model based information systems, learning and hypothesis formation, natural language and other man-machine communication, space manufacturing, teleoperators and robot systems, and computer science and technology

Supporting web programming assignment assessment with test automation and RPA

Automated software solutions to support and assist in assessment of student implemented applications are not a rarity, but often need to be custom engineered to fit a specific learning environment or a course. When such a system can be fielded in use properly, it has a tremendous potential to lighten the workload of course personnel by automating the repetitive manual tasks and testing student submissions against assignment requirements. Additionally, these support systems are often able to shorten the feedback loop which is seen to have a direct impact on student learning. In this thesis test automation and robotic process automation are researched to discover how they can be used to support web programming assignment assessment. The background on software testing, automation and feedback related pedagogy are researched mainly by the methods of literature review and expert interview. A third methodology – design science – is then applied for the purpose of verifying and extending the learnt theory in an empirical manner. A research artifact is created in the form of a prototype capable of supporting in assessment tasks. Performance of the prototype is measured by recording set execution metrics while assessing anonymized case study student submissions from a web development course arranged by University of Turku: DTEK2040 Web and Mobile Programming. Thesis concludes that to support assessment through test automation is to focus on unit and system level testing of functionalities while assuming the exact implementation at code level cannot be fully known. Suggestion is made that relying on assignment descriptions as basis for test design is not enough, but rather requirements engineering should be done together with course personnel to take advantage of their experience in what sort of errors are to be tolerated in student submissions. Thesis also concludes that automation can perform interaction with student submissions, file manipulation, record keeping and tracking tasks at a satisfactory level. The potential to shorten the feedback loop and summarizing quantitative feedback for the student is recognized, however, to build an automated system to identify, gather and summarize formative, pedagogically more valuable feedback was noted to be out of scope for this thesis and suggested as future work to possibly extend the prototype with.Automatisoidut ohjelmistoratkaisut, jotka tukevat ja avustavat opiskelijoiden toteuttamien sovellusten arvioinnissa, eivät ole harvinaisia, mutta ne useimmiten joudutaan rakentamaan tiettyyn oppimisympäristöön tai opintosisältöön sopiviksi. Tällaiset järjestelmät omaavat kuitenkin valtavan potentiaalin keventää kurssihenkilöstön työtaakkaa automatisoimalla toistuvia manuaalisia työtehtäviä ja automaatiotestaamalla opiskelijoiden palauttamia tuotoksia asetettuja tehtävävaatimuksia vastaan. Järjestelmät johtavat varsin usein myös opiskelijan näkökulmasta nopeampaan palautesykliin, jolla kyetään todeta olevan suora vaikutus oppimiseen. Tässä opinnäytetyössä tutkitaan testiautomaatiota sekä robottiprosessiautomaatiota pyrkimyksenä selvittää kuinka näitä teknologioita voitaisiin hyödyntää tukemaan web-ohjelmointitehtävien arviointia. Ohjelmistotestauksen, automaation ja palautteen pedagogiikan taustoja tutkitaan pääasiassa kirjallisuuskatsauksen ja asiantuntijahaastattelun menetelmin. Lisäksi sovelletaan kolmatta metodologiaa, suunnittelutiedettä, jonka tavoitteena on vahvistaa teoriaosuuden havaintoja sekä pyrkiä empiirisesti laajentamaan niitä. Suunnittelutieteen kautta tutkimusartifaktina syntyy prototyyppi, jonka suorituskykyä ja hyötyjä mitataan keräämällä dataa hyödyntäen aitoja, anonymisoituja opiskelijapalautuksia Turun yliopiston järjestämän DTEK2040: Web and Mobile Programming -kurssin tiimoilta. Opinnäytetyön johtopäätöksenä on, että arvioinnin tukeminen testiautomaation avulla on keskittymistä yksikkö- ja järjestelmätason toiminnallisuuksien testaukseen. Testaukseen on liitettävä myös oletus, että arvioitavan kohteen tarkkaa toteutusta kooditasolla ei voida täysin tuntea. Tehtäväkuvausten käyttö testitapausten suunnittelun perustana todetaan riittämättömäksi, ja vaatimussuunnittelu ehdotetaan tehtävän yhdessä kurssin henkilökunnan kanssa, jotta heidän kokemuksiaan voidaan hyödyntää yleisimpien opiskelijapalutuksissa ilmenevien virhetapausten kartoittamiseksi sekä testitapausten tarkkuuden ja arvioinnin jyrkkyyden säätämiseksi. Prosessiautomaation osalta todetaan, että automaatio kykenee suorittamaan vuorovaikutusta opiskelijoiden palautusten, tiedostojen käsittelyä, kirjanpito- ja seurantatehtäviä tyydyttävällä tasolla. Mahdollisuus palautesilmukan lyhentämiseen ja summaavan palautteen yhteenvetoon opiskelijalle tunnustetaan myös empiirisesti. Laadullisen, pedagogisesti arvokkaamman palautteen kokoaminen ja jalostaminen todettiin tämän opinnäytetyön mittakaavassa liian suureksi projektiksi ja sen empiiristä toteutusta ehdotettiin yhtenä mahdollisena jatkotutkimusaiheena