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What is communication (and what isn’t it)?
The P21 framework emphasizes the effective use of oral, written, and nonverbal communication skills for multiple purposes (e.g., to inform, instruct, motivate, persuade, and share ideas). It also focuses on effective listening, using technology to communicate, and being able to evaluate the effectiveness of communication efforts—all within diverse contexts (adapted from P21). Note that working in partners is a great way to collaborate or build shared understanding but a critical part of communication is sharing with an authentic audience.
Example strategies that use technology to support communication in the classroom:

Host a TED-style conference or showcases for your students to present original ideas on a topic of interest to them to an authentic, external audience. Record and post the videos to a youtube stream.
Provide opportunities to listen and ask questions through backchannel tools like Today’s Meet or even Twitter.

 

Have your students publish their work through blogs, by creating websites, and by building other online resources that are shared with authentic audiences.
For other ideas see the resources below.

https://youtu.be/KUM4AECEcUA
 

The basic idea of intelligence:An explosion is that once machines reach a certain level of intelligence, they’ll be able to work on AI just like we do and improve their own capabilities — redesign their own hardware and so on — and their intelligence will zoom off the charts. There’s an area emerging called “cyber-physical systems” about systems that couple computers to the real world. With a cyber-physical system, you’ve got a bunch of bits representing an air traffic control program, and then you’ve got some real airplanes, and what you care about is that no airplanes collide. You’re trying to prove a theorem about the combination of the bits and the physical world. What you would do is write a very conservative mathematical description of the physical world — airplanes can accelerate within such-and-such envelope — and your theorems would still be true in the real world as long as the real world is somewhere inside the envelope of behaviors.
Yet you’ve pointed out that it might not be mathematically possible to formally verify AI systems.
There’s a general problem of “undecidability” in a lot of questions you can ask about computer programs. Alan Turing showed that no computer program can decide whether any other possible program will eventually terminate and output an answer or get stuck in an infinite loop. So if you start out with one program, but it could rewrite itself to be any other program, then you have a problem, because you can’t prove that all possible other programs would satisfy some property.

Categories of AI
Artificial intelligence:
can be divided into two different categories: weak and strong. Weak artificial intelligence embodies a system designed to carry out one particular job. Weak AI systems include video games such as the chess example from above and personal assistants such as Amazon's Alexa and Apple's Siri. You ask the assistant a question, it answers it for you.
 
Strong artificial intelligence systems are systems that carry on the tasks considered to be human-like. These tend to be more complex and complicated systems. They are programmed to handle situations in which they may be required to problem solve without having a person intervene. These kinds of systems can be found in applications like self-driving cars or in hospital operating rooms.
 
 

common myths
for Advanced
AI:A captivating conversation is taking place about the future of artificial intelligence and what it will/should mean for humanity. There are fascinating controversies where the world’s leading experts disagree, such as AI’s future impact on the job market; if/when human-level AI will be developed; whether this will lead to an intelligence explosion; and whether this is something we should welcome or fear. But there are also many examples of boring pseudo-controversies caused by people misunderstanding and talking past each other. 

TIMELINE MYTHS



The first myth regards the timeline: how long will it take until machines greatly supersede human-level intelligence? A common misconception is that we know the answer with great certainty.
One popular myth is that we know we’ll get superhuman AI this century. In fact, history is full of technological over-hyping. Where are those fusion power plants and flying cars we were promised we’d have by now? AI has also been repeatedly over-hyped in the past, even by some of the founders of the field. For example, John McCarthy (who coined the term “artificial intelligence”), Marvin Minsky, Nathaniel Rochester, and Claude Shannon wrote this overly optimistic forecast about what could be accomplished during two months with stone-age computers: “We propose that a 2 month, 10 man study of artificial intelligence be carried out during the summer of 1956 at Dartmouth College […] An attempt will be made to find how to make machines use language, form abstractions, and concepts, solve kinds of problems now reserved for humans, and improve themselves. We think that a significant advance can be made in one or more of these problems if a carefully selected group of scientists work on it together for a summer.”

CONTROVERSY MYTHS



Another common misconception is that the only people harboring concerns about AI and advocating AI safety research are Luddites who don’t know much about AI. When Stuart Russell, author of the standard AI textbook, mentioned this during his Puerto Rico talk, the audience laughed loudly. A related misconception is that supporting AI safety research is hugely controversial. In fact, to support a modest investment in AI safety research, people don’t need to be convinced that risks are high, merely non-negligible — just as a modest investment in home insurance is justified by a non-negligible probability of the home burning down.

Global education helps
students develop their capacity to be informed, open-minded, and responsible people, who are responsive to diverse perspectives. Global education prepares us to address the world’s most pressing issues collaboratively, equitably, and sustainably. Global education helps students understand that pressing issues must be faced in an interdisciplinary way, given the complexity of environments and competing needs and interests.
 
The primary aim of Global Citizenship: Education (GCED)  is nurturing respect for all, building a sense of belonging to a common humanity, and helping learners become responsible and active global citizens. GCED aims to empower learners to assume active roles to face and resolve global challenges and to become proactive contributors to a more peaceful, tolerant, inclusive, and secure world. Education for global citizenship helps young people develop the core competencies which allow them to actively engage with the world and help make it a more just and sustainable place. It is a form of civic learning that involves students’ active participation in projects that address global issues of a social, political, economic, or environmental nature.

Educator provides evidence
of their understanding of communication and outlines and provides evidence of a lesson that uses technology to support students’ use of communication in learning.
Method Components
What are the 4Cs?
The 4Cs for 21st century learning are Creativity, Critical Thinking, Communication, and Collaboration. They are part of the framework for 21st Century Learning and are designed to support student learning in today’s world and are skills they can use in college and career.
What is communication (and what isn’t it)?
The P21 framework emphasizes effective use of oral, written, and nonverbal communication skills for multiple purposes (e.g., to inform, instruct, motivate, persuade, and share ideas). It also focuses on effective listening, using technology to communicate, and being able to evaluate the effectiveness of communication efforts—all within diverse contexts (adapted from P21). Note that working in partners is a great way to collaborate or build shared understanding but a critical part of communication is sharing with an authentic audience.
Example strategies that use technology to support communication in the classroom:

Host a TED-style conference or showcases for your students to present original ideas on a topic of interest to them to an authentic, external audience. Record and post the videos to a youtube stream.
Provide opportunities to listen and ask questions through back channel tools like Today’s Meet or even Twitter.
Have your students publish their work through blogs, by creating websites, and by building other online resources that are shared with authentic audiences.
For other ideas see the resources below.

Reflection
Prompt

Were you successful in providing opportunities for students? Why or why not? What improvements or revisions could be included?
How did you provide instruction and formative feedback on these habits, skills, and dispositions to students along the way?
If you were to embed habits, skills, and/or dispositions in another performance, what would you do differently from this time?

Competency Info
The Advanced Performance Assessment for Learning
Design stack is designed so that, if all three credentials are taken together, they will become more than the sum of their parts. Each micro-credential is intended to be able to stand on its own; however, the ideas and activities of each of these credentials support and expand on the others, allowing a fuller appreciation of performance assessment and its implications. Even more value will be gained by engaging in all three Performance Assessment for Learning stacks together.
Habits, Skills, and Dispositions:
Habits, Skills, and Dispositions are those qualities that—in addition to academic knowledge - are necessary for success in college, career, and civic life. Examples include collaboration, creativity, communication, and self-direction, among others. Increasingly, these habits, skills, and dispositions are seen as essential for the success of students in college, career, and civic life (for more, see the infographic in the resources). They are referred to in the field by a number of names, including essential skills and dispositions, work-study habits, non-cognitive skills, etc.
Performance assessments that measure habits, skills, and dispositions provide students with feedback on how well developed these essential skills are and how they might improve performance.