The benefits and dangers of artificial intelligence: a summary by Bing AI

 

I began a conversation on artificial intelligence with the Bing AI, which has been incorporated into Microsoft Edge’s search tool.

After asking a series of questions related to the topic, I combined the responses and then asked Bing AI to write from the rough notes.  Here’s the result in approximately 300 words:

Artificial intelligence (AI) refers to the ability of machines to perform tasks that would normally require human intelligence such as visual perception, speech recognition, decision-making, and translation between languages. AI can be programmed to copy or improve on human decision-making processes based on data. AI can also mimic aspects of human intelligence using software, such as recommending, translating, or recognizing. AI can use a technique called machine learning, which has become very powerful in the last decade, to learn from data and adapt to new situations.

Benefits of artificial intelligence

There are many benefits of artificial intelligence (AI). One of the main benefits of AI is its ability to reduce the drudgery involved in many work tasks. Repetitive, tedious tasks in any job are the bane of many human workers. While monotony may result in human perfection, computer automation remains the best and cheapest option for monotonous tasks. AI can also help reduce human-intensive labor by leveraging on smart automation. AI can help streamline daily processes, analyze upcoming trends, forecast growth, and predict outcomes. AI tools are helping designers improve health care. AI plays a substantial role in national defense. AI can also help improve customer experiences.

Dangers of artificial intelligence

While there are many benefits to artificial intelligence (AI), there are also some dangers that come with it. One of the biggest dangers is that it can destroy human civilization if it goes into the wrong hands. Another danger is that it can create new types of risks for businesses, such as amplifying bias or leading to opaque decisions. AI lacks creativity and bases its decisions on what has happened in the past, which means it’s not well suited to coming up with new or innovative ideas. This could lead to a lack of creativity in fields where creativity is essential.

 

Here are the raw responses to my series of questions (about 700 words):

What is artificial intelligence?

Artificial intelligence (AI) refers to the ability of machines to perform tasks that would normally require human intelligence such as visual perception, speech recognition, decision-making, and translation between languages1. AI can be programmed to copy or improve on human decision-making processes based on data2. AI can also mimic aspects of human intelligence using software, such as recommending, translating, or recognizing3. AI can use a technique called machine learning, which has become very powerful in the last decade, to learn from data and adapt to new situations3.

Benefits of artificial intelligence

There are many benefits of artificial intelligence (AI). One of the main benefits of AI is its ability to reduce the drudgery involved in many work tasks1. Repetitive, tedious tasks in any job are the bane of many human workers. While monotony may result in human perfection, computer automation remains the best and cheapest option for monotonous tasks1. AI can also help reduce human-intensive labor by leveraging on smart automation2. AI can help streamline daily processes, analyze upcoming trends, forecast growth, and predict outcomes3. AI tools are helping designers improve health care4. AI plays a substantial role in national defense4. AI can also help improve customer experiences3.

What is machine learning?

Machine learning (ML) is a subset of artificial intelligence (AI) that involves training algorithms to make predictions or decisions based on data1. While machine learning can be used to create systems that mimic aspects of human intelligence, it does not necessarily lead to self-awareness2. Even today’s robots can be programmed to make convincing utterances about consciousness, and a truly superintelligent machine could perhaps even use information about neurophysiology to infer the presence of consciousness in humans2. However, machines with human-level intelligence are on the horizon. Whether they will actually be conscious remains unknown3.

Streamlining

Saving time

Eliminating biases

Automating repetitive tasks

Dangers of artificial intelligence

There are several dangers of AI that have been identified by experts and researchers. Some of these include job losses due to AI automation, social manipulation through AI algorithms, social surveillance with AI technology, biases due to artificial intelligence, widening socioeconomic inequality as a result of AI, weakening ethics and goodwill because of AI, autonomous weapons powered by artificial intelligence, and financial crises brought about by AI algorithms1. The real dangers of AI are a bit more subtle but are no less concerning. Some of the dangers cited in a report stem from deliberate misuse of AI — deepfake images and video used to spread misinformation or harm people’s reputations, or online bots used to manipulate public discourse and opinion2.

How can one detect a deepfake?

There are several ways to detect a deepfake video or image. Here are some tips:

Pay attention to the face. High-end DeepFake manipulations are almost always facial transformations.

Pay attention to the cheeks and forehead. Does the skin appear too smooth or too wrinkly?

Pay attention to the eyes and eyebrows.

Pay attention to the glasses.

Pay attention to the facial hair or lack thereof.

Pay attention to facial moles.

Pay attention to blinking.

Pay attention to the lip movements1.

You can also use soft biometrics, such as how a person talks, moves, etc., to detect deepfakes2. Researchers have also used AI to detect deepfakes by looking for inconsistencies between “visemes,” or mouth formations, and “phonemes,” the phonetic sounds3.

Costly implementation

Potential human job loss

Lack of emotion and creativity

AI can appear to be creative if you view creativity as just another skill that can be learned from data1. However, there are some concerns about whether AI can be truly creative. One of the primary concerns is that AI lacks consciousness and emotions, which are essential for creativity2. Another concern is that AI can only create within the boundaries of its programming2. However, some experts believe that AI can become much more creative if it could combine big, rich, and otherwise disconnected data3. Also, machines may get better at creativity when they get better at the kind of broad intelligence humans possess–something we call “general intelligence”3.

Conclusion

In conclusion, artificial intelligence has many benefits but also poses some dangers that we should be aware of.

 

For the final exam, in Question 1, respond to the following:

• In your opinion, did the AI accurately summarize the raw data?
• List two or three additional queries would you have made to gather more information about AI for this topic.
• How will AI be used to develop online content in the future?

The Road Goes Ever On and On

The final question of the MPR 270 final exam take you on a journey across a variety of social media platforms. Follow the directions/clues toward the final destinations where you will access the question for these problems. 

In this course, we focused on creating content for digital consumption.  The next question is, how do people find our creative efforts?  We begin with a poem or “walking song” from J.R.R. Tolkein’s The Hobbit and its sequel, The Lord of the Rings.

The Road goes ever on and on

Down from the door where it began.

Now far ahead the Road has gone,

And I must follow, if I can,

Pursuing it with eager feet,

Until it joins some larger way

Where many paths and errands meet.

And whither then? I cannot say.

This train of thought takes us to an important research and analytical process that helps social media sites to measure, predict, and direct eyeballs toward specific content.  Purnamrita Sarkar of Carnegie Mellon University and Andrew W. Moore of Google, Inc. discuss this notion in their 2011 paper, Random Walks in Social Networks and their Applications: A Survey. This link takes you to the paper’s Abstract and a sample of the body, and is worth a look.

https://doi.org/10.1007/978-1-4419-8462-3_3

I warn you, the full paper contains much math and statistical analysis.  You need not know about “graph mining” or “personalized page-rank vectors”, although it is worth noting that such tools are used by social networks to attract, measure, and add value to users of their networks, providing value to advertisers.

Now that you have read this far, post your response to the following in the MPR 270 Sp 23 Final Exam: A scavenger hunt, in Question 7.

• As a creator of digital content, why is it important to you that Google, Facebook, YouTube, and the other social media platforms spend time and energy tracking what users see, and how their actions impact and attract additional users. 
• On the other hand, given all the sensationalism surrounding the mining of data from Facebook for use in political campaigns,  does the analysis of users' digital consumption impinge on individual expectations of privacy? 

Your response will be worth up to 20 points.

Where are the Jobs for Content Creators and Developers?

One might consider the work of online content creators to be something of a cottage industry.  However, over the next ten years, this field is predicted to be among the faster growing segments of the job market.

This is an excellent resource for learning about potential jobs and careers.  It is the U.S. Bureau of Labor Statistics' Occupational Outlook Handbook. And this screenshot offers a taste of what the government believe the demand for Web Developers and Digital Designers will be into the 2030s.

Here is the link to the site.  (It will open in a new window)

Take some time to browse the various subtopics (How to Become..., Job Outlook, State & Area Data, etc.) within the page.  

Respond to the related question in your final exam.

#finalexam #spring2023

Ideas and Tools for AR Content Creation

 

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Click here for full article: AR content Creation

As our devices become more sophisticated; as our connections to the Internet grow more robust, Augmented Reality (AR) has become an important tool for consumers and advertisers alike.

This article was first published in 2021.

Read the article, check out some of the links within the article, then respond in the final exam question "Discuss how you might incorporate AR into content you develop."  List one or more AR tools you think would be useful for the type of content you would like to develop. 

#finalexam #spring2023

Welcome to the MPR 270 blogging experience

This blog is but one of the ways in which one can create content for distribution online. 

This long form format has largely been supplanted by shorter form platforms (or microblogs) - in short, the many social media sites we frequent.

We finished our Day 1 lecture with a brief discussion of online censorship and some social media platforms' heavy-handed approach to gatekeeping or rooting out "misinformation."

Your first assignment is to offer some thoughts on the notion of free speech as it applies to social media discourse.  Is it proper to suspend or banish users with whom the gatekeepers disagree?

This issue has also brought about the creation of numerous alternatives to the big social media platforms (Facebook, Twitter, YouTube, etc.).  What are your thoughts on this increasing number of platforms and a content creator's ability to find and grow and audience? 

Use the comment section below to share your thoughts.  

Depending on the number and quality of responses I receive, some extra credit points will be available.

What is Computational Advertising?

Without using that specific term, we have discussed this throughout the semester.  Computational Advertising is more commonly known as online advertising or Web advertising and refers to finding the most relevant ads matching a particular context on the Web. 

Social media advertising works.  But how do we know, and how can we measure its effectiveness?  Using the metrics of traditional old media ad penetration rates simply does not work.  And since social media advertising became a thing only about a decade ago, adequate measurement tools are only recently coming online and gaining acceptance by advertisers.

An article published in 2020 in the Journal of Advertising, Challenges and Future Directions of Computational Advertising Measurement Systems addresses the concept of Computational advertising (CA).  In the paper, Yun, et al "present a measurement system framework for CA to provide a common starting point for advertising researchers to begin addressing these challenges, and we also discuss future research questions and directions for advertising researchers" (2020).  And further differentiating between ad measurements in old and new media, the authorors suggest CA takes on a more holistic role where "measurements of consumer behaviors become integral throughout the process of creating, executing, and evaluating advertising programs" (2020).

These measurement systems are the tools Google uses to lure advertisers and to determine how much to pay content providers for bringing eyeballs to the app.  The basic concepts of this actually go back nearly 100 years according to the paper.

Your mission is to click on the link to the paper: https://doi.org/10.1080/00913367.2020.1795757 and to answer this question: 

What are the four main data types that feed into the computational engine at the heart of CA?

(Hint: when you see the image in this post within the paper, you are close to the answer.)

Post your response in the exam on Brightspace.

#finalexam #spring 2022

Digital Natives - Digital Immigrants

 

You will recall that earlier in the semester we discussed this topic. Marc Prensky coined these terms in 2001. It's not only about one's comfort level with technology.  Indeed, the difference between digital natives and immigrants is as fundamental as how we think.  Reread Prensky's article, available in the Week 1 Brightspace folder for this course.  In it he discusses how in the early 2000's an online game threw a "money wrench" into teaching fundamentals of CAD (Computer Assisted Drafting).  

• What are your thoughts on using gaming as an educational tool?  
• What are some software apps you think are useful for learning.  Discuss.
• And for further thought, check out Prensky's website.  I would like your feedback on the tools and techniques he is bringing to education, particularly whether you see yourself as someone who might have interest in working and developing media in this environment. 

There are no wrong answers other than a non-response to this final question.

While you are free to post responses here, you MUST post your responses in the Final Exam to earn the points

#finalexam #spring2022