It is early days for generative art AIs. What are some ways to use these to complement one's work while staying legal (legal-ish)?
Correction: .webp is a raster format
Fashioning Text (and Image) Prompts for the CrAIyon Art-Making Generative AIShalin Hai-Jew
CrAIyon (formerly DALL-E after Salvador “Dali”) is a web-facing art-making generative AI tool online (https://www.craiyon.com/) that enables the uses of text (and image) prompts for the creation of watermarked, lightweight visuals. Counterintuitively, the rough visuals are much more usable for recombinations and remixes and recreations into usable digital visuals for various digital learning objects. The textual prompts are not particularly intuitive because of how the generative AI program was trained on mass-scale visuals). There is an art and occasional indirection to working prompts after each try, with the resulting nine-image proof sheets that CrAIyon outputs. The tool can be used iteratively for different outputs.
The tool sometimes turns out serendipitous surprises, including an occasional work so refined that it can be used / shared almost unedited. One challenge in using CrAIyon comes from their request for credit (for all non-subscribers to their service). Another comes from the visual watermarking (orange crayon at the bottom right of the image). However, this tool is quite useful for practical applications if one is willing to engage deep digital image editing (Adobe Photoshop, Adobe Illustrator).
Creating Seeding Visuals to Prompt Art-Making Generative AIsShalin Hai-Jew
Art-making generative AIs have come to the fore. A basic work pipeline typically involves starting with text prompts -> generated images. That image may be used to seed further iterations. Deep Dream Generator (DDG) enables the application of “modifiers” of various types (artist styles, visual adjectives, others) to be applied in addition to the text prompt.
Another approach involves beginning with a “seeding image,” a born-digital or digitized (born-analog) visual on which AI-generated art may be based for a multi-channel and multi-modal prompt. This slideshow provides some observations of how to think about seeding images, particularly in terms of how the DDG handles them, with its “algorithmic pareidolia” (“Deep Dream,” Wikipedia, July 3, 2023).
Human art-making is often about throwing mass-scale conversations. Artists are thought to help bridge humanity into the future. Whether generative AI art enables this or not is still not clear.
Some Ways to Conduct SoTL Research in Augmented Reality (AR) for Teaching and...Shalin Hai-Jew
One of the extant questions about augmented reality (AR) is how (in)effective it is for the teaching and learning in various formal, nonformal, and informal contexts. The research literature shows mixed findings, which are often highly context-based (and not generalizable). There are some non-trivial costs to the design/development/deployment of AR for teaching and learning. For the users, there is cognitive load on the working memory [(1) extraneous/poor design, (2) intrinsic/inherent difficulty in topic, and (3) germane/forming schemas]. For teachers, there are additional knowledge, skills, and abilities / attitudes (KSAs) that need to be brought to bear.
Exploring the Deep Dream Generator (an Art-Making Generative AI) Shalin Hai-Jew
The Deep Dream Generator was created by Google engineer Alexander Mordvintsev in 2014. It has a public facing instance at https://deepdreamgenerator.com/, which enables people to use text prompts and image prompts (individually or in combination) to inspire the art-generating generative AI to output images. This work highlights some process-based walk-throughs of the tool, some practical uses, some lightweight art learning, some aspects of the online social community on this platform, and other insights. Some works by the AI prompted by the presenter may be seen here: https://deepdreamgenerator.com/u/sjjalinn.
(This is the first draft of a slideshow that will be used in a conference later in the year.)
An introductory take on the ethical issues surrounding the use of algorithms and machine learning in finance, education, law enforcement and defense. This work was stimulated by, but is not a product or authorized content from the IEEE P7003 WG.
Disclaimer: This work is mine alone and does not reflect view of IEEE, IEEE 7003 WG, my employer.
The field of Artificial Intelligence (AI) has progressed rapidly in the past few years. AI systems are having a growing impact on society and concerns have been raised whether AI system can be trusted. A way to address these concerns is to employ ethically aligned design principles to the development of AI software. Yet these principles are still far away from practical application. This talk provides state-of-the-art empirical insight into what should researchers and professionals do today when the client wants ethics to be added to their system.
Co-Creating Common Art with AI Tools in Adobe Photoshop 2022Shalin Hai-Jew
Artificial intelligence (AI) has been applied to various methods for digital image creation and editing in Adobe Photoshop 2022. “Inartful” common art and digital photos can be re-imagined using such “neural filters” as style transfer, landscape mixer, color transfer, harmonization, Depth Blur, colorization, and others. The filters can be additive or reductive, or both (of various elements). This session offers walk-throughs of these various Neural Filter features in Adobe Photoshop 2022 (using AI Adobe Sensei). Come explore the “imagination” in a digital image editing software.
Fashioning Text (and Image) Prompts for the CrAIyon Art-Making Generative AIShalin Hai-Jew
CrAIyon (formerly DALL-E after Salvador “Dali”) is a web-facing art-making generative AI tool online (https://www.craiyon.com/) that enables the uses of text (and image) prompts for the creation of watermarked, lightweight visuals. Counterintuitively, the rough visuals are much more usable for recombinations and remixes and recreations into usable digital visuals for various digital learning objects. The textual prompts are not particularly intuitive because of how the generative AI program was trained on mass-scale visuals). There is an art and occasional indirection to working prompts after each try, with the resulting nine-image proof sheets that CrAIyon outputs. The tool can be used iteratively for different outputs.
The tool sometimes turns out serendipitous surprises, including an occasional work so refined that it can be used / shared almost unedited. One challenge in using CrAIyon comes from their request for credit (for all non-subscribers to their service). Another comes from the visual watermarking (orange crayon at the bottom right of the image). However, this tool is quite useful for practical applications if one is willing to engage deep digital image editing (Adobe Photoshop, Adobe Illustrator).
Creating Seeding Visuals to Prompt Art-Making Generative AIsShalin Hai-Jew
Art-making generative AIs have come to the fore. A basic work pipeline typically involves starting with text prompts -> generated images. That image may be used to seed further iterations. Deep Dream Generator (DDG) enables the application of “modifiers” of various types (artist styles, visual adjectives, others) to be applied in addition to the text prompt.
Another approach involves beginning with a “seeding image,” a born-digital or digitized (born-analog) visual on which AI-generated art may be based for a multi-channel and multi-modal prompt. This slideshow provides some observations of how to think about seeding images, particularly in terms of how the DDG handles them, with its “algorithmic pareidolia” (“Deep Dream,” Wikipedia, July 3, 2023).
Human art-making is often about throwing mass-scale conversations. Artists are thought to help bridge humanity into the future. Whether generative AI art enables this or not is still not clear.
Some Ways to Conduct SoTL Research in Augmented Reality (AR) for Teaching and...Shalin Hai-Jew
One of the extant questions about augmented reality (AR) is how (in)effective it is for the teaching and learning in various formal, nonformal, and informal contexts. The research literature shows mixed findings, which are often highly context-based (and not generalizable). There are some non-trivial costs to the design/development/deployment of AR for teaching and learning. For the users, there is cognitive load on the working memory [(1) extraneous/poor design, (2) intrinsic/inherent difficulty in topic, and (3) germane/forming schemas]. For teachers, there are additional knowledge, skills, and abilities / attitudes (KSAs) that need to be brought to bear.
Exploring the Deep Dream Generator (an Art-Making Generative AI) Shalin Hai-Jew
The Deep Dream Generator was created by Google engineer Alexander Mordvintsev in 2014. It has a public facing instance at https://deepdreamgenerator.com/, which enables people to use text prompts and image prompts (individually or in combination) to inspire the art-generating generative AI to output images. This work highlights some process-based walk-throughs of the tool, some practical uses, some lightweight art learning, some aspects of the online social community on this platform, and other insights. Some works by the AI prompted by the presenter may be seen here: https://deepdreamgenerator.com/u/sjjalinn.
(This is the first draft of a slideshow that will be used in a conference later in the year.)
An introductory take on the ethical issues surrounding the use of algorithms and machine learning in finance, education, law enforcement and defense. This work was stimulated by, but is not a product or authorized content from the IEEE P7003 WG.
Disclaimer: This work is mine alone and does not reflect view of IEEE, IEEE 7003 WG, my employer.
The field of Artificial Intelligence (AI) has progressed rapidly in the past few years. AI systems are having a growing impact on society and concerns have been raised whether AI system can be trusted. A way to address these concerns is to employ ethically aligned design principles to the development of AI software. Yet these principles are still far away from practical application. This talk provides state-of-the-art empirical insight into what should researchers and professionals do today when the client wants ethics to be added to their system.
Co-Creating Common Art with AI Tools in Adobe Photoshop 2022Shalin Hai-Jew
Artificial intelligence (AI) has been applied to various methods for digital image creation and editing in Adobe Photoshop 2022. “Inartful” common art and digital photos can be re-imagined using such “neural filters” as style transfer, landscape mixer, color transfer, harmonization, Depth Blur, colorization, and others. The filters can be additive or reductive, or both (of various elements). This session offers walk-throughs of these various Neural Filter features in Adobe Photoshop 2022 (using AI Adobe Sensei). Come explore the “imagination” in a digital image editing software.
Generative AI art has a lot of issues:
Lack of Control: Generative AI art eliminates digital artists' control over their work. The results are unpredictable and often unsatisfactory, leaving artists feeling frustrated.
No Unique Signature: Generative AI art lacks a unique signature or style, making it difficult for digital artists to stand out.
Quality Control Issues: Generative AI art can be of poor quality and unsuitable for professional use. Digital artists who rely on their work to make a living may find that AI-generated work is not up to their standards.
Decreased Job Opportunities: As generative AI art becomes more popular, the demand for human digital artists may decrease, leading to fewer job opportunities.
No Emotional Connection: Generative AI art lacks the emotional connection artists can create through their work. This can make it difficult for digital artists to connect with their audience and make a lasting impact.
Limited Creative Potential: Generative AI art has limited creative potential based on algorithms and pre-defined parameters. Digital artists who seek to express their creativity and individuality may find it limiting.
Intellectual Property Concerns: Generative AI art can infringe on the intellectual property of others, leading to legal issues for the artist.
Lack of Personal Touch: Generative AI art lacks the personal touch that digital artists can bring to their work. This can result in a lack of emotion, connection, and engagement with the audience.
Decreased Income: Generative AI art is often available for free or at a low cost, making it difficult for digital artists to make a living through their work.
Loss of Craftsmanship: Generative AI art relies on technology, taking away the element of craftsmanship and hand-drawn skills that digital artists have honed over time.
[DSC DACH 23] ChatGPT and Beyond: How generative AI is Changing the way peopl...DataScienceConferenc1
In recent years, generative AI has made significant advancements in language understanding and generation, leading to the development of chatbots like ChatGPT. These models have the potential to change the way people interact with technology. In this session, we will explore the advancements in generative AI. I will show how these models have evolved, their strengths and limitations, and their potential for improving various applications. Additionally, I will show some of the ethical considerations that arise from the use of these models and their impact on society.
For this plenary talk at the Charlotte AI Institute for Smarter Learning, Dr. Cori Faklaris introduces her fellow college educators to the exciting world of generative AI tools. She gives a high-level overview of the generative AI landscape and how these tools use machine learning algorithms to generate creative content such as music, art, and text. She then shares some examples of generative AI tools and demonstrate how she has used some of these tools to enhance teaching and learning in the classroom and to boost her productivity in other areas of academic life.
This slide shows (1) AI and Accountability , (2) AI Ethics, (2) Privacy Protection. Several AI ethics documents such as IEEE EAD, EC-HELG Ethics Guideline for Trustworthy AI, Social Principles of Human-Centric AI(Japan), focus on AI's transparency, accountability and trust. We follow the discussions of these documents around the above (1),(2) and (3) topics.
This collection of slides are meant as a starting point and tutorial for the ones who want to understand AI Ethics and in particular the challenges around bias and fairness. Furthermore, I have also included studies on how we as humans perceive AI influence in our private as well as working lives.
A Glimpse Into the Future of Data Science - What's Next for AI, Big Data & Ma...Pangea.ai
We are living in the era of "the fourth industrial revolution". How did we get here? Read this presentation to explore current application trends in Artificial Intelligence (AI,) The Internet of Things (IoT), Big Data, and Machine Learning (ML) technology. Also, to discover the future implications of big data in our lives.
Read the original article here: https://www.pangea.ai/data-science-resources/future-of-data-science/
Work with a data science expert at Pangea: https://www.pangea.ai/
This presentation reflects on ChatGPT and how it affects us as a whole, not just technically. Discover the truths about AI and the impacts it has per some of today's top tech professionals.
Can ChatGPT be compatible with the GDPR? Discuss.Lilian Edwards
Since the Italian Garantie became the first DP authority in the world to even temporarily ban ChatGPT, debate has broken out as to whether generative AI models can comply with data protection laws, not just in the GDPR but around the world. The use of personal data for training requires a legal basis which is hard to find, special category data raises special problems (duh) and the model itself may be considered personal data due to inversion attacks and data leakage in outputs. Hallucination presents seemingly insuperable problems as to accuracy and rectification. Even though Open AI have temporarily satisfied the Garantie, further disputes still seem likely to eventually reach the courts. In this talk I will attempt to throw the entirety of DP law against the wall of large language and image models and even, jut for fun, raise the spectre of whether AI models can libel
Some Preliminary Thoughts on Artificial Intelligence - April 20, 2023.pdfKent Bye
Bye, K. (2023, April 20). Some Preliminary Thoughts on Artificial Intelligence. [Presentation] The King Library Experiential Virtual Reality Lab (KLEVR) Tech Talks: AI Tools, Tips, & Traps; San Jose State University, San Jose, California via Zoom.
3D reconstructions for story telling and understandingCARARE
This slidedeck was prepared for a webinar exploring some of the ways that 3D reconstructions are being used for story telling and to aid understanding. Following an introduction to the webinar Daniel Pletinckx of Visual Dimension bvma gave a presentation on 'Interactive storytelling in virtual worlds' which is followed by a presentation by Catherine Cassidy of the Open Virtual Worlds group at the University of St Andrews on 'Dissemination Methods for 3D Historical Virtual Environments'.
Tech Trends 2024 and Beyond - AI and VR and MOreBrian Pichman
Join Brian Pichman, the tech geek from the Evolve Project, in a
jolly tech-filled sleigh ride through the hottest trends that'll make
this holiday season merrier for librarians! From digital AI elves
to magical augmented reality, this fun-packed presentation will
unwrap the tech wonders that'll keep libraries ahead of the
game in the North Pole of innovation. Don't miss out on the
holiday cheer and the chance to sprinkle some digital snow on
your library's future!
Generative AI art has a lot of issues:
Lack of Control: Generative AI art eliminates digital artists' control over their work. The results are unpredictable and often unsatisfactory, leaving artists feeling frustrated.
No Unique Signature: Generative AI art lacks a unique signature or style, making it difficult for digital artists to stand out.
Quality Control Issues: Generative AI art can be of poor quality and unsuitable for professional use. Digital artists who rely on their work to make a living may find that AI-generated work is not up to their standards.
Decreased Job Opportunities: As generative AI art becomes more popular, the demand for human digital artists may decrease, leading to fewer job opportunities.
No Emotional Connection: Generative AI art lacks the emotional connection artists can create through their work. This can make it difficult for digital artists to connect with their audience and make a lasting impact.
Limited Creative Potential: Generative AI art has limited creative potential based on algorithms and pre-defined parameters. Digital artists who seek to express their creativity and individuality may find it limiting.
Intellectual Property Concerns: Generative AI art can infringe on the intellectual property of others, leading to legal issues for the artist.
Lack of Personal Touch: Generative AI art lacks the personal touch that digital artists can bring to their work. This can result in a lack of emotion, connection, and engagement with the audience.
Decreased Income: Generative AI art is often available for free or at a low cost, making it difficult for digital artists to make a living through their work.
Loss of Craftsmanship: Generative AI art relies on technology, taking away the element of craftsmanship and hand-drawn skills that digital artists have honed over time.
[DSC DACH 23] ChatGPT and Beyond: How generative AI is Changing the way peopl...DataScienceConferenc1
In recent years, generative AI has made significant advancements in language understanding and generation, leading to the development of chatbots like ChatGPT. These models have the potential to change the way people interact with technology. In this session, we will explore the advancements in generative AI. I will show how these models have evolved, their strengths and limitations, and their potential for improving various applications. Additionally, I will show some of the ethical considerations that arise from the use of these models and their impact on society.
For this plenary talk at the Charlotte AI Institute for Smarter Learning, Dr. Cori Faklaris introduces her fellow college educators to the exciting world of generative AI tools. She gives a high-level overview of the generative AI landscape and how these tools use machine learning algorithms to generate creative content such as music, art, and text. She then shares some examples of generative AI tools and demonstrate how she has used some of these tools to enhance teaching and learning in the classroom and to boost her productivity in other areas of academic life.
This slide shows (1) AI and Accountability , (2) AI Ethics, (2) Privacy Protection. Several AI ethics documents such as IEEE EAD, EC-HELG Ethics Guideline for Trustworthy AI, Social Principles of Human-Centric AI(Japan), focus on AI's transparency, accountability and trust. We follow the discussions of these documents around the above (1),(2) and (3) topics.
This collection of slides are meant as a starting point and tutorial for the ones who want to understand AI Ethics and in particular the challenges around bias and fairness. Furthermore, I have also included studies on how we as humans perceive AI influence in our private as well as working lives.
A Glimpse Into the Future of Data Science - What's Next for AI, Big Data & Ma...Pangea.ai
We are living in the era of "the fourth industrial revolution". How did we get here? Read this presentation to explore current application trends in Artificial Intelligence (AI,) The Internet of Things (IoT), Big Data, and Machine Learning (ML) technology. Also, to discover the future implications of big data in our lives.
Read the original article here: https://www.pangea.ai/data-science-resources/future-of-data-science/
Work with a data science expert at Pangea: https://www.pangea.ai/
This presentation reflects on ChatGPT and how it affects us as a whole, not just technically. Discover the truths about AI and the impacts it has per some of today's top tech professionals.
Can ChatGPT be compatible with the GDPR? Discuss.Lilian Edwards
Since the Italian Garantie became the first DP authority in the world to even temporarily ban ChatGPT, debate has broken out as to whether generative AI models can comply with data protection laws, not just in the GDPR but around the world. The use of personal data for training requires a legal basis which is hard to find, special category data raises special problems (duh) and the model itself may be considered personal data due to inversion attacks and data leakage in outputs. Hallucination presents seemingly insuperable problems as to accuracy and rectification. Even though Open AI have temporarily satisfied the Garantie, further disputes still seem likely to eventually reach the courts. In this talk I will attempt to throw the entirety of DP law against the wall of large language and image models and even, jut for fun, raise the spectre of whether AI models can libel
Some Preliminary Thoughts on Artificial Intelligence - April 20, 2023.pdfKent Bye
Bye, K. (2023, April 20). Some Preliminary Thoughts on Artificial Intelligence. [Presentation] The King Library Experiential Virtual Reality Lab (KLEVR) Tech Talks: AI Tools, Tips, & Traps; San Jose State University, San Jose, California via Zoom.
3D reconstructions for story telling and understandingCARARE
This slidedeck was prepared for a webinar exploring some of the ways that 3D reconstructions are being used for story telling and to aid understanding. Following an introduction to the webinar Daniel Pletinckx of Visual Dimension bvma gave a presentation on 'Interactive storytelling in virtual worlds' which is followed by a presentation by Catherine Cassidy of the Open Virtual Worlds group at the University of St Andrews on 'Dissemination Methods for 3D Historical Virtual Environments'.
Tech Trends 2024 and Beyond - AI and VR and MOreBrian Pichman
Join Brian Pichman, the tech geek from the Evolve Project, in a
jolly tech-filled sleigh ride through the hottest trends that'll make
this holiday season merrier for librarians! From digital AI elves
to magical augmented reality, this fun-packed presentation will
unwrap the tech wonders that'll keep libraries ahead of the
game in the North Pole of innovation. Don't miss out on the
holiday cheer and the chance to sprinkle some digital snow on
your library's future!
An overview of the most important AI capabilities in marketing, advertising and content creation. I made this presentation to inform, educate and inspire people in the creative industries to familiarise themselves with the incredible toolsets that are already here and in development. I also explain how generative Ai works explore some possible new roles and business models for agencies. Hope you enjoy it!
machines will be capable, within 20 years, of doing any work a man can do." Two years later, MIT researcher Marvin Minsky predicted, "Within a generation ... the problem of creating 'artificial intelligence' will substantially be solved."
(artificial intelligence innovator Herbert Simon.1965
AI tools in Scholarly Research and PublishingBrian Pichman
Discover how AI is revolutionizing research methodologies and publishing processes, making data analysis more efficient and streamlining academic workflows. This talk will cover the latest trends, challenges, and future opportunities of integrating AI in academia. Ideal for scholars, publishers, and tech enthusiasts aiming to stay ahead in the digital age. We will also explore new tools and how to build your own environments.
My presentation today about ChatGPT, Open AI, conversational AI, and the Future Of Work. Includes survey data from the audience. Presented at our Constellation Research Execution Network monthy Office Hours of CIOs, CDOs, and other CXOs.
This is a PPT which highlights the basics of artificial intelligence and how it works and will affect job scenario.
ai in drug discovery, artificial intelligence, artificial intelligence in drug discovery, deep learning, deep learning techniques, gan, generative adversarial network (gan), gpu, gpu (graphics processing unit)-, graphics processing units, machine learning, matconvent, nvidia, nvidia dgx-1, python, tensorflow, torche, IBM watson for drug discovery
machine learning in drug discovery, deep learning in drug discovery
AI for Nonprofits What You Need to Know-.pdfTechSoup
In this webinar, nonprofits learned the latest generation of AI by Microsoft, what these tools can do for mission-focused work ,and the need to use them in a thoughtful, responsible manner.
Our guest speakers, Joshua Pesky, and Destiny Bowers from Roundtable Technology shared an understanding of what AI is, the different kinds of AI that exist, use cases for nonprofits, and thoughtful strategies for this emerging tech.
AUGMENTING CREATIVITY USING GEN AI FOR DESIGN & INNOVATION | TOJIN T. EAPENTojin Eapen, PhD
Presentation slides from my September 2023 guest lecture on Generative AI and its impact on creativity. The lecture also highlights the key themes of my recent July/August 2023 Harvard Business Review (HBR) cover article, exploring the potential of Generative AI to enhance human creativity. Additionally, the presentation engages in a discussion regarding the emerging opportunities and challenges within this domain.
Generative AI (GAI) refers to a type of artificial intelligence that is able to generate new data or content, such as text, images, or music. This is typically done by training a model on a large dataset of existing data, and then using the model to generate new, similar data.
-Promote Divergent Thinking
-Challenge Expertise Bias
-Assist in Idea Evaluation
-Support Idea Refinement
-Facilitate Collaboration
https://hbr.org/2023/07/how-generative-ai-can-augment-human-creativity
One of the biggest opportunities generative AI offers to businesses and governments is to augment human creativity and overcome the challenges of democratizing innovation.
AI Workshops at Computers In Libraries 2024Brian Pichman
While AI holds tremendous potential for libraries, it also comes with significant concerns and the potential for harm. We find ourselves sailing uncertain waters; there are few guardrails governing AI's use. Even as we acknowledge this truth, we must also note that library staff are already experimenting with the use of AI chatbots (most commonly ChatGPT), generative AI design tools (like Midjourney), and other variations of AI technology. In short, we have great potential, pitfalls, and a total lack of clarity. It is only through the thoughtful development of policy, procedure, and professionals that we can hope to articulate a vision for the ethical use of AI in our libraries. Join this conversation about new disruptive technology, take a deep breath, and get to work laying a foundation of policy guidelines and staff development to navigate the uncertain road ahead.
This interactive and hands-on workshop allows you to play and experiment with new tools which will spark ideas for the future of your library and community activities. It focuses on OpenAI’s API and how to get started building personalities in AI. It explores various tools to create AI images, videos, and more. Filled with tips, it will definitely be fun!
UX in the Age of AI: Leading with Design UXPA2018Carol Smith
How can designers improve trust of cognitive systems? What can we do to make these systems transparent? What information needs to be transparent? The biggest challenges inherent with AI will be discussed, specifically the ethical conflicts and the implications for your work, along with the basics of these concepts so that you can strive for making great AI systems.
20240104 HICSS Panel on AI and Legal Ethical 20240103 v7.pptxISSIP
20240103 HICSS Panel
Ethical and legal implications raised by Generative AI and Augmented Reality in the workplace.
Souren Paul - https://www.linkedin.com/in/souren-paul-a3bbaa5/
Event: https://kmeducationhub.de/hawaii-international-conference-on-system-sciences-hicss/
Similar to Human-Machine Collaboration: Using art-making AI (CrAIyon) as cited work, or inspiration, reference, base (20)
Long nonfiction chapters are not in-style and may never have been. Where average chapter lengths of nonfiction book chapters are about 4,000 – 7,000 words in length, some may be several times that max range number. The explanation is that there is some irreducible complexity that that chapter addresses that cannot be addressed in shorter form. This slideshow explores some methods for writing longer chapters while still maintaining coherence, focus, and reader interest…and while using some technological tools to write and edit more efficiently.
Overcoming Reluctance to Pursuing Grant Funds in AcademiaShalin Hai-Jew
Starting as an organization’s new grant writer can be a challenge, especially in a case where there has been a time lapse since the last one left. People get out of the habit of pursuing grant funds. This slideshow addresses some of the reasons for such reluctance and proposes some ways to mitigate these.
Writing grants is one common way that those in institutions of higher education may acquire some funds—small and big, one-off and continuing—to conduct research, hire faculty and researchers and learners and others, update equipment, update or build up new buildings, and achieve other work. This slideshow explores some aspects of the work of grant writing in the present moment in higher education.
Contrasting My Beginner Folk Art vs. Machine Co-Created Folk Art with an Art-...Shalin Hai-Jew
The SARS-CoV-2 pandemic inspired several years of experimentation with common or folk art, involving mixed media, alcohol ink painting, and other explorations. Then, with the emergence of art-making generative AIs, there were further experiments, particularly with one that enables generation of visuals from scanned art and photos, text prompts, style overlays, and text-based visual modifiers. While both types of artmaking are emotionally satisfying and helpful for stress management, there are some contrasting differences. This exploratory slideshow explores some of these differences in order to partially shed light on the informal usage of an art-making generative AI (artificial intelligence).
Common Neophyte Academic Book Manuscript Reviewer MistakesShalin Hai-Jew
The work of academic book reviewing, as a volunteer (most often), is a common academic practice. The presenter has served as a neophyte one for some years before settling into this invited volunteer work for several decades. There have been lessons learned over time about avoidable mistakes…from both experience and observation.
Augmented Reality in Multi-Dimensionality: Design for Space, Motion, Multiple...Shalin Hai-Jew
Augmented reality (AR)—the use of digital overlays over physical space—manifests in a wide range of spaces (indoor, outdoor; virtual) and ways (in real space (with unaided human vision); in head gear; in smart glasses; on mobile devices, and others). There are various authoring technologies that enable the making of AR experiences for various users. This work uses a particular tool (Adobe Aero®) to explore ways to build AR for multiple dimensions, including the fourth dimension (motion, changes over time).
Based on the respective purposes of the AR experience, some basic heuristics are captured for
space design (1),
motion design (2),
multiple perception design (sight, smell, taste, sound, touch) (3),
and virtual- and tangible- interactivity (4).
Augmented Reality for Learning and AccessibilityShalin Hai-Jew
Recently, the presenter conducted a systematic review of the academic literature and an environmental scan to learn how to set up an augmented reality (AR) shop at an institution of higher education. The ambition was to not only set up AR in an accessible and legal way but also be able to test for potential +/- effects of AR on teaching and learning. The research did not go past the review stage, because of a lack of funding, but some insights about accessibility in AR were acquired.
(The visuals are from Deep Dream Generator and CrAIyon.)
Engaging Pixabay as an open-source contributor to hone digital image editing,...Shalin Hai-Jew
This slideshow describes the author's early experiences with creating two accounts on Pixabay in order to advance digital editing skills in multimedia. The two accounts are located at https://pixabay.com/users/sjjalinn-28605710/ and https://pixabay.com/users/wavegenerics-29440244/ ...
This work explores four main spaces where researchers publish about educational technology: academic-commercial, open-access, open-source, and self-publishing.
Getting Started with Augmented Reality (AR) in Online Teaching and Learning i...Shalin Hai-Jew
University creative shops are exploring whether they can get into the game of producing AR-enhanced experiences: campus tours, interactive gaming, virtual laboratories, exploratory art spaces, simulations, design labs, online / offline / blended teaching and learning modules, and other AR applications.
This work offers a basic environmental scan of the AR space for online teaching and learning, and it includes pedagogical design leads from the current research, technological knowhow, hands-on design / development / deployment of learning objects, and online teaching and learning methods.
Co-Creating Common Art with the CrAIyon AIShalin Hai-Jew
This slideshow contains a variety of images created using the CrAIyon AI...based on seeding terms. This work asks questions about common art in an age of AI.
This is the revised intro to Adobe Animate set of notes used in a training in late June 2022. The Word version is downloadable from www.k-state.edu/ID/AdobeAnimateHandout.docx, with the motion available from the animated .gifs.
"Drift" is the latest in the alcohol ink drip playing series. After reaching the first learning plateau a year and a half in, I am finding second wind. This is all still fun.
100% “Tier 0” in a Year? Supporting Graduate Students’ ETDRs w/ DocumentationShalin Hai-Jew
Video: https://vimeo.com/716175153
What I.T. challenge involves novel research, data, sensitive information, and global reputations? Complex Microsoft Word templates? LaTeX templates? Evolving technologies? Dozens of source citation methods? Local domain-based conventions? Professorial quirks? Multiple web-facing databases? Hard deadlines that can be costly if missed?
Electronic theses, dissertations, and reports, better known as ETDRs!
This presentation describes a real-world context in which a core staff retirement (and the role’s non-replacement) resulted in the need for fast learning of the ETDR space and an effort to enable graduate student work with thorough documentation, updated templates, and web conferences, in the backdrop of the pandemic. The solution here is only partial, and the challenge is still being worked, but some objective progress may be seen.
Mapping Narrative Structures w/ Computational Text Analysis (LIWC-22)Shalin Hai-Jew
A classic narrative (storytelling) structure begins at a start point, builds tension, reaches a point of climax, and then achieves resolution. This structure is found in many texts, written and spoken. LIWC-22 (pronounced “luke”) enables a computational analysis of various texts for various indicators of narrative structure, specifically, staging, plot progression, and cognitive (psychological) tensions. Come see how this tool is applied to various texts and how the resulting information may be used for research and analysis.
This slideshow "Teardrop" is the latest in the alcohol ink drip playing series started in Jan. 2021 as a relief from the pressures of the pandemic. This work is likely the last in the series. I plan to keep on experimenting with common art.
A Light Intro to Adobe Character Animator 2022Shalin Hai-Jew
If it has seemed difficult to make talking characters for videos, the Adobe Character Animator might be just the software app for you. This tool offers a variety of rigged puppet characters—animal, human, object—that can be animated through movements of a webcam…and can emulate mouth motions linked to speech (visemes, sound). These are glorious “shallow fakes,” but they are eye-catching and lots of fun. The various motions and sounds may be exported as individual keyframes for usage in video sequences and other applications (including live-streaming in character). Adobe Character Animator originally came out in 2015.
The Metaverse and AI: how can decision-makers harness the Metaverse for their...Jen Stirrup
The Metaverse is popularized in science fiction, and now it is becoming closer to being a part of our daily lives through the use of social media and shopping companies. How can businesses survive in a world where Artificial Intelligence is becoming the present as well as the future of technology, and how does the Metaverse fit into business strategy when futurist ideas are developing into reality at accelerated rates? How do we do this when our data isn't up to scratch? How can we move towards success with our data so we are set up for the Metaverse when it arrives?
How can you help your company evolve, adapt, and succeed using Artificial Intelligence and the Metaverse to stay ahead of the competition? What are the potential issues, complications, and benefits that these technologies could bring to us and our organizations? In this session, Jen Stirrup will explain how to start thinking about these technologies as an organisation.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
7. Presentation Overview
Generative AI can create natural language text in various formats and
voices and perspectives (ChatGPT) and emulative style-transferred
visual images (CrAIyon, DALL-E, MidJourney, and others).
Controversies are swirling around various aspects of generative AI.
7
8. Presentation Overview (cont.)
How the generative AI tools are made and run:
• uses of copyrighted seeding texts and visuals in databases to train the
AIs (without the permission of the original authors, in some cases),
• guardrails around generative contents (such as those against x-rated
content, against hate speech, against various dimensioned
stereotypes, etc.) vs. those without any guardrails,
8
9. Presentation Overview (cont.)
How the generative AI tools are used:
• academic honesty, citations,
• commercial applications,
• authorship and crediting (and rewards and liabilities)
9
10. Presentation Overview(cont.)
• A typical sequence in using a text-seeded generative AI that creates
digital visuals is to use seeding phrases to describe the desired visual
(often multiple iterations)…selecting the image…downloading the
image as a .webp (“weppy”) format (neither raster nor vector), and
directly using the image with citation…or using the image as an
inspiration, reference, or base. (One creates a derived image, by
borrowing some visual concepts from the generative AI.)
“Photorealistic” asks the AI for create an image that looks like an
actual photo. “after Picasso” or “in the style of Georgia Totto
O’Keeffe” asks for a style transfer from the known works of the artist
into a different context.
10
11. Presentation Overview (cont.)
• [Please see “Co-Creating Common Art with the CrAIyon AI” on
SlideShare: https://www.slideshare.net/ShalinHaiJew/cocreating-
common-art-with-the-craiyon-ai for a clearer visual gist of this
phenomenon.]
• The presenter wrote an article titled “CrAIyon: Putting an art-making
AI through its paces” on the C2C Digital Magazine at
(https://scalar.usc.edu/works/c2c-digital-magazine-fall-2022---winter-
2023/craiyon-paces). As a former college faculty member and current
instructional designer, the presenter introduces the topic and throws
a conversation around the complexities.
11
13. What are some text prompts that you might
use with CrAIyon?
• Remember that this tool enables a wide range of languages and
symbols and combinations.
• This tool can engage in “style transfer,” so if you have a particular
visual artist you like, you can evoke that artist’s name.
• You can evoke various materials that you want the generative AI to
produce.
• Go a few rounds. Iterate from your original text prompt. Or try some
highly variant prompts.
• Any visuals worth downloading (.webp)?
13
14. Impressions? (first or otherwise)
• What are you noticing about the machine-generated visuals?
• Did anyone try “photorealistic” as one of their prompts?
• Did anyone try “after” a particular artist style?
• Did anyone try a particular material effect?
14
15. Impressions? (first or otherwise) (cont.)
• Do you feel like you could export something practically useful?
Impractically useful?
• What do you like? Why?
• What do you dislike? Why?
• What are some practical applications for you?
15
16. Impressions? (first or otherwise) (cont.)
• Are you starting to notice some visual tropes that the AI has?
• Whare are some strengths of the generative AI (based on
impressions)? What are some weaknesses?
• If you could change the tool capabilities, what would you do, and
why?
16
19. Generative AI…
• …refers to computational programs that emulate humans by
generating various content (text, audio, imagery, motion visuals,
video, and other elements, including combines audiovisual ones)
• The AI programs learn through large samples of big data, so it can
emulate nuances of understandings…although such programs are in
early years (some compare them to “teenagers”).
19
20. Generative AI (cont.)
• Generative adversarial networks (GANs) do not only generate
contents to particular objectives, but they have a built-in test of
quality / veracity to desired outcomes against which the generative
aspect strives to improve.
• Generative AI can generate content into ∞ and beyond, but there
may not be enough human attention (attention economy) to enjoy
the various works. The works need to be meaningful to humans.
20
21. Human in the Loop
• As it stands, the generative AIs may be prompted in a mix of ways:
• Textual prompts to help the AI know what is desirable in terms of visuals, so it
can output various visuals for consideration
• Visual prompts to help the AI have examples of the visual gist and perhaps
content that may be desirable, so it can output various visuals for
consideration
• Combined inputs (textual and visual)
• And others
21
23. Debate around Human-Machine
“Collaboration”
• How much is the human responsible for the artwork vs. the
computing machine?
• Does the computing machine have an agentic role given its design as
“artificial intelligence”?
• Does it matter if the work is run unedited directly from the generative
AI download?
• Does it matter if the work is edited and changed, superficially?
• Does it matter if the work is edited and changed, down to the pixel level?
23
24. Debate around Human-Machine
“Collaboration” (cont.)
• Who has the first idea (remember that the machine can turn out
something serendipitous and unconceptualized by the person who
inputs the prompt)?
• What if the content (text or visual) is created sui generis (unique, one-of-a-
kind) by the computing machine?
• What if the content (text or visual) is created ex nihilo (from nothing,
specifically without inputs by people’s works or by people’s prompts)?
• Who is responsible for the aesthetics? The composition? The social
angle? And why?
• Who is the “animating agent” and why?
24
25. …And Credit
Human
• Traditionally, artists are credited
for original single-artist and
team-created fine artworks.
• The artist’s name and
personality and history serve as
an artist brand.
Machine
• Can AI be credited for (fine and
other) artworks?
• What are the implications for
renown? For money? For
payment? For prizes?
• Should the programmers behind
an art-making AI be credited for
the artworks?
25
26. …And Reward…and Liability
Human
• In tradition, the artist bears
responsibility for the work to
some degree…and then the
owner thereafter…
Machine
• In tradition, computing
machines do not generally bear
reward or liability. Rather, their
owners do.
26
27. Reapportionment of Credit? Rewards?
Liabilities?
27
• Should credit be reapportioned? Rewards? Liabilities?
28. Drawing Lines…Or Not…
• How should schools address generative AI?
• How should professions? (How can people show their value
especially while in competition with generative AI works?)
• How should publishers?
• Or is this too soon to start drawing lines?
28
32. Q1: How would you use generative AI in your
respective contexts?
• And then, do you feel the need to disclose that you use an AI for
assistance or some other reason?
• Do you count neural filters (in digital image editing) as AI (after all,
various neural networks were used to tune the digital image editing, to
transfer styles, to recolor photos, to change hue / saturation, to change
the depth-of-field, to enable deep zoom, to enable facial editing, and
others)?
32
33. Q2: If you teach or edit, what would your
policies be about generative AI? Why?
• Explain why your policy is timely…but fair…and pro-learner / pro-
author (or researcher).
• How would you differentiate something that is created from
generative AI vs. not?
• What are ways to manage this issue of generative AI in teaching and
learning?
33
34. Q3: What can learners learn from generative
AI if it is harnessed as a learning tool?
• Given the state of the world, with advanced technologies coming to
the fore in the 4IR (Fourth Industrial Revolution), how can people
adapt and better position themselves for these fast-arriving changes?
• How would you as a learner harness generative AI?
• Are there ways to make generative AI more friendly for learners?
• Much of generative AI has been democratized, with free web-facing portals
and apps. Are there other ways to extend the benefits to the world?
34
35. Q4: What are some ways to position for the
impact of generative AI on human jobs?
• Generative AI is thought to squelch some white-collar jobs while
creating other jobs. What do you see as the possible impact of
generative AI on your particular work and professional circumstance?
Why?
• If you have funds to retrain, how would you use those funds?
• What are some other AIs and technologies on the horizon that may
well have a big impact on the near-future? The mid-term future?
35
40. Some Real-Life Applications
Practical: Visuals in an Open-Source,
Open-Access Magazine
• An open-source and open-access
publication needs some light visuals
to break up the gray text.
• I have gone through social imagery
datasets and not found anything that
the author likes.
• I go to generative AI to output a few
ideas, and then I create a visual image
to use with the generated image as an
inspiration or a reference image (used
for its lines which I capture via trace).
Impractical: Amusement,
Entertainment
• I want to be amused. I can go to a
generative AI with various text prompts
to see what it will output. Some can be
highly surprising and funny. (Generative
AIs can have a strange sense of physics
and bodies and hands and eyes.)
• A generative AI can offer high
entertainment value.
40
41. Some Real-Life Applications(cont.)
Practical: Learning about Digital Image
Editing
• I am practicing digital image editing. I
want to learn new functions in some
very complex digital image editing
software.
• I create some unusual prompts, and
then I use the imagery to apply new
learning.
• I also want to learn more about
AI…and how it interacts with language.
Impractical: Open-Sharing of Social
Imagery
• I want to create visuals for open-
sharing on the Social Web. I
conceptualize an idea…and generate
some images…and then use those
images to serve as references for an
original visual.
• Anything used more directly is
credited as from AI.
41
42. Some Real-Life Applications(cont.)
Practical: Learning about Visual
Thinking
• In other times, I want to learn how to
create moods and other visual effects.
The generative AI can offer fresh
insights.
• Ditto with various visual
communications messages…some
banal…and some more creative…
• Sometimes, I want to understand
word definitions in a visual sense.
Impractical: Wasting Time
• In between work, sometimes, it helps
to just put in a text prompt and have
the generative AI doodle something
(in under 2 minutes).
• Sometimes, there is the additional
benefit of learning…but a distraction
is sometimes very welcome.
42
43. Some Initial Personal Observations
• There is not a straight-line to the visual I usually want, which tends to
be somewhat artsy and strange.
• Iterating from an initial prompt with additional prompts may not get me much
closer.
• Word order only seems to matter sometimes.
• It does help to know the lingo for digital image editing and analog image
making (sketching, drawing, painting, mixed media, and others).
• The generative AI is too often literal and less symbolic and less
figurative. It is almost never poetic.
• Occasionally, there is a fluke that can result in something very
aesthetically pleasing and unexpected.
43
44. Some Initial Personal Observations (cont.)
• The generative AI, CrAIyon, IMHO, has its own quirks and signatures
(based on my half-year of experiences with it).
• It draws famous (and non-famous people badly, with weird eyes and bad hands
when it is trying to be “photorealistic”.
• It has a hard time drawing human proportions, too.
• It draws animals poorly, without a real-world sense of anatomy.
• It blurs much of a small image. (Blurring reads as non-committal.)
• It seems to like spirals to stand in for something precise.
• It does not do clean gridlines.
• It does not seem to do gradients.
44
45. Some Initial Personal Observations (cont.)
• It seems to have some bias towards spooky things.
• It sometimes goes full-bore stereotypical.
• It sometimes pulls people in its own quirky universe instead of aligning with the
real world.
• Between figurative and abstract, it seems to do the middle ground fairly well
but not those on the extreme ends.
• It does not handle text (probably there is some throttling back against
the uses of any language…so it has a doodle-y version of its own).
45
46. Some Initial Personal Observations (cont.)
Some of my purposeful and unpurposeful misadventures:
• When I typed in “fairytales for men,” the AI generated 9 visuals of
men in various fashion walking down catwalks.
• When I typed in “wild,” the generative AI came up with a variety of
apparent mammals that do not exist except in its own imagination.
These are patchwork animals, with patches of skin, some horns,
different hooves, and so on.
46
47. Some Initial Personal Observations (cont.)
• Truth to tell, I am mostly generally impressed and appreciative.
47
49. The Upsides
• So to end on an upside, I like CrAIyon because of the following:
• It is always game. Whatever prompt I put in, it always kicks up something.
• It outputs visuals I can practically use in most cases.
• It sometimes outdoes itself and offers me something that is easy to make look
artful. [But this is after years of my work in the digital image editing space.]
• It is surprising now and again.
49
50. The Upsides (cont.)
• While it has challenges with some shapes, it composites well.
• It handles values (lights and darks) well.
• I think it’s working on its color sensibilities. Often, it can be quite
muted. It does not take risks in its color choices.
50
51. The Upsides (cont.)
• I for one will keep right on learning…because it helps to be ready.
And this saves so much on time and analog art materials. Well, I do
have some time sinks where I spend an hour digitally editing a work
until I am satisfied.
• We should test limits…
• My uses of generative AI (currently) are for “artwork” with a lower-
case “a,” nothing aspiring to high art. My uses are for common art.
51
52. A Caveat
• Generative AI really does make my life somewhat easier when I have
to chase images, but the jury (general public, decision makers, and
others) is still out about the uses of generative AI-supported
visuals…so perhaps we need to see how the world shapes out in
terms of its approaches.
52
55. Conclusion and Contact
• Dr. Shalin Hai-Jew
• Instructional Design
• ITS
• Kansas State University
• 785-532-5262
• shalin@ksu.edu
• Note: All the visuals in the slideshow (save the cross-functional
diagram) were seeded with CrAIyon visuals but edited pretty heavily
in Adobe Illustrator and Adobe Photoshop. Some could have run
unedited, but I wanted to change these up from the originals.
55