To refresh my mind on where I have got to in the development of this project I reviewed weeks 1-4.

This covered the following:


— How is this relevant to my practice?
— What am I doing and why am I doing it?
— What's my intention/goal?
— Can the project effect change for good?
— How does my own experience, story, values and understanding play a part?

— Redefine the positioning and reasoning for my approach (Context).
— Immerse myself in my theme/research question.



HISTORICAL: 1984-Present Day.
Example: First things First (Ken Garland/Adbusters).

Stakeholders: Designers, Design Founders, Computer Scientists (Adobe?).
Statistics: From design bodies.
Ethics: Understanding what safeguards are already in place.

— Seek dialogue with stakeholders.

Research question: How will AI shape the future of design practice?
— How can I use, archives, artefacts, language, voices and user experiences?
— Who else is working in this field?
— What social, political, cultural and environmental concerns can be unpacked?
— What are the ethics of AI?


Post Research

— How do I use the data to implement radical strategies for enacting a plan/vision?
— What insights/patterns can be found?
— Are there any parties who would be interested in my research findings?
— How can I provide tools for the community to continue to effect change?


Visual Storytelling: The Evolution of Graphic Design in the Age of AI (excerpts)
— Graphic design has evolved in response to societal changes and technological advancements.
— At the heart of graphic design lies visual storytelling.
— The digital age marked a pivotal turning point, enabling designers to explore new frontiers with computer software and digital tools.
— AI = unprecedented transformation in graphic design.
— Innovative tools that amplify creativity.
— Access to AI-driven software that analyzes trends, anticipates user preferences, and generates designs with remarkable precision.‚
— Automates repetitive tasks, liberating designers from mundane chores.
— Freedom to focus more on ideation and conceptualization.
— Elevated visual storytelling.
— AI-generated images can evoke emotions and resonate with audiences, as seen in social media campaigns and digital advertisements.
Website design: AI tools can analyze user behavior and preferences, tailoring the visual elements of a website to create a seamless and engaging user experience.
— AI also raises challenges and ethical considerations.
— Reliance on AI may stifle human creativity, leading to a homogenized design landscape.
— Authenticity of AI-generated artwork raises questions about authorship and originality.
— AI efficiency and human ingenuity crucial to preserving the essence of graphic design.
— Virtual reality (VR) and augmented reality (AR) are poised to revolutionize visual storytelling, enabling audiences to immerse themselves in captivating narratives like never before.
— Democratization of design through online platforms has enabled freelance designers to thrive in this evolving landscape.


The Evolution of Graphic Design: A Year in Review with AI (Excerpts)
— Companies like Adobe, Canva, and Figma have incorporated machine learning algorithms to enhance and streamline the creative process.
— Tools leverage AI to automate repetitive tasks, suggest design elements, and even generate entire layouts, allowing designers to focus more on conceptualization and innovation.
— AI can analyse vast datasets, identify patterns, and generate unique design variations based on specified criteria.
— AI has empowered designers to create highly personalized and targeted designs by leveraging user data.
— Designers can now tailor their creations to individual preferences and behaviors.
— Enhances user experiences.
— Enables brands to establish deeper connections with their audiences.
— Designers can now create immersive and interactive experiences, allowing users to engage with visual content in unprecedented ways.
— AI algorithms play a crucial role in optimizing and enhancing these virtual environments, providing a seamless and captivating user experience.
— Style transfer algorithms enable designers to apply the characteristics of one artwork or style to another, fostering a unique fusion of artistic influences.
Ethical concerns: Bias in AI algorithms, intellectual property issues, and the displacement of design jobs.


Introduction: The Rise of AI in Graphic Design (Excerpts)
— Collaborative partner, augmenting the creative process rather than replacing it.
— AI algorithms can identifying common patterns and trends.
— AI can generate design recommendations that align with a specific brand’s aesthetic or target audience preferences.
— Provides designers with fresh ideas and inspiration, expanding their creative repertoire.
Technologies and techniques: machine learning, language processing, computer vision, and more.
— Algorithms are used to analyze data, recognize patterns, and make intelligent decisions.
— Increases productivity but also frees up time for designers to experiment with new ideas and push the boundaries of their creativity.
— Augments designers’ capabilities, streamlining workflows, and fostering innovation.
— Empowers designers to u stay ahead in a rapidly evolving digital landscape.
Automated image editing: designers can streamline their workflow by automating tasks like retouching, color correction, and background removal.
— AI can make intelligent adjustments to achieve the desired color balance and tone.
— AI can recognise different objects and elements within an image.
Generative AI: Generates unique and creative designs based on user inputs and predefined parameters. Designers can guide the AI system to generate designs that meet their criteria.
— Goes beyond what a human designer might conceive and allows designers to explore unconventional ideas and unexpected design solutions.
Brainstorming assistant: By inputting specific parameters and design preferences, AI provides a wealth of inspiration to explore.
— Constant source of inspiration. AI helps designers stay up-to-date with the latest trends and gain fresh perspectives.
— AI systems can adapt and customise the design elements of a website, app, or digital platform to suit individual users.
— Enhances user engagement and satisfaction, leading to improved user experiences.
— Should AI be allowed to create designs that infringe upon copyrighted material?
— How can we determine whether an AI-generated design is a result of independent creation or a mere copy?
— It may be necessary to develop new regulations or guidelines specifically tailored to the unique challenges posed by AI in graphic design.
— Collaboration between AI developers and legal experts can help establish mechanisms to ensure that AI-generated designs respect and protect the rights of original creators.
— AI’s ability to mimic human creativity makes it increasingly difficult to discern whether a design was created by a human or an AI system.
— Concerns about the value and integrity of design work.
Transparency and disclosure are crucial: designers and AI developers should clearly communicate when AI systems are involved in the design process.
— Establishing standards for labeling AI-generated designs can help differentiate them from purely human creations, ensuring transparency and preserves the integrity of the design industry.
Autonomous AI: designers input their requirements and preferences, which generates a multitude of options in seconds. Would save designers hours of brainstorming and sketching and a broader range of ideas to choose from.
— human creativity is irreplaceable. Design is not just about aesthetics; it is about storytelling, emotion, and connecting with the audience on a deeper level.
— AI lacks the ability to understand context, culture, and human experiences.
— Human designers possess a unique ability to think critically, make subjective judgments, and infuse their designs with personal meaning.
— Designers have the capacity to adapt and respond to changing trends, cultural shifts, and individual client needs.
— Designers need to ensure that AI remains a tool that serves the creative vision rather than dictating it.
— The future of graphic design lies in the hands of designers who embrace AI as a complementary tool.
— By combining human creativity with technological advancements, designers can unlock new levels of innovation and create designs that resonate with audiences on a deeper level.


The rise of AI in the graphic design industry: What does it mean to graphic design agencies? (Excerpts)
Design Research Society (DRS), founded in the UK in 1966, claims to be “the longest established, multi-disciplinary worldwide society for the design research community”. Its purpose is to promote the study and research of the process of designing and to bring together a community based on shared interests in new approaches to the process of designing.

— AI can be seen as threatening to deskill the graphic design profession with the emphasis on fast turnover and functional artefact production.
— Graphic design integrally linked to technology from the emergence of desktop publishing in the 1980s to designers engaging with interactive multimedia and online communication from the 1990s onwards.
— Increasing integration of automation into graphic design including future developments in AI present new challenges for graphic design agencies.
— Computer science approach to AI and graphic design: automation within professional commercial software, amateur template-driven design tools, and experimental—academic research into graphic design.
— AI within professional graphic design software has tended to focus on automating laborious tasks allowing designers more opportunity to focus on the creative side of projects.
— AI advancements come from a computer science-based discipline that focuses on functionality and task-driven practices.
— Graphic design agencies add many other components such as the acknowledgement of a creative brief that indicates the direction, the subject matter, the intended audience, its role and intended use.
— Graphic design agencies engage in thinking about audience or consumer considerations, briefing process and discussion, creative concepts, stakeholder interaction, branding and identity, creative reflection, client engagement, and topic research.
— Current AI research tends to engage with the functional stage of graphic design processes such as task automation, production process, functionality and layout, and artefact outcome.
— Historically it has been necessary for graphic designers and graphic design agencies to embrace a balancing act between creativity and technology.
— Current successful advances entrenched in time saving automation and machine learning for the design software tools themselves.
— Despite the potential threat of deskilling, still allows graphic designers creative control of projects.


The Impact of AI Design Tools on Graphic Design and Creativity (Excerpts)
— According to a report by Adobe, 62% of creative professionals believe that AI will be a fundamental part of their work within five years.
— A study by McKinsey & Company reveals that AI-driven design processes can lead to a 10-30% reduction in design production costs.
— In a survey by 99designs, 64% of designers agreed that AI design tools help them be more productive, but 58% were concerned about job security.
— AI design tools enhance efficiency and expand design possibilities but should be used responsibly.
— Designers must continuously learn about AI capabilities and ethical considerations.
— The future of graphic design lies in the harmonious coexistence of AI and human creativity.
— The history of graphic design is marked by a journey from traditional, labor-intensive methods to the digital age.
— As designers once relied on hand-drawn illustrations and physical media, they now harness the capabilities of AI to streamline workflows and unlock new horizons of creative expression.
— The graphic design landscape underwent a significant transformation with the advent of digital technology.
— The introduction of computers and graphic design software in the late 20th century marked a pivotal moment.
— Designers transitioned from traditional tools to digital platforms, enabling them to work more efficiently and experiment with new design possibilities.
— This shift democratised design to some extent, as it became more accessible to a broader audience.
— One of the challenges posed by AI in graphic design is the potential dependency on AI tools.
— Over-dependence on AI may lead to a lack of creativity and innovation, as designers may start to rely on pre-built templates and automated suggestions
— Striking a balance between utilising AI for efficiency and preserving the designer’s creative input is essential.
— Ethical considerations: the manipulation of images to create deepfakes, which can be used for deceptive or harmful purposes.
— Responsible AI usage and ethical design practices are essential to address these concerns.
— Concerns about its potential impact on employment in the industry.
— There may be shifts in job roles and responsibilities within the design field.
— AI image editing software like Adobe Photoshop and Adobe Lightroom now incorporate AI-driven features.
— Democratizes design, making it more accessible to individuals with varying levels of expertise.
— Generative adversarial networks (GANs) are at the forefront of AI-generated artwork. GANs consist of two neural networks, a generator, and a discriminator, which work in tandem to produce original images.
— AI can present designers with a range of logo concepts based on industry trends and historical data.
— This raises concerns about the quality and appropriateness of the designs produced.
— Designers worry that AI might produce designs that are culturally insensitive, offensive, or inappropriate for certain contexts.
— Designers and AI developers should collaborate to ensure that AI-generated designs align with ethical and cultural norms.
— Bias in AI design tools is a significant ethical concern.
— AI systems can inadvertently perpetuate biases present in the data they are trained on, leading to discriminatory or exclusionary outcomes.
— Promoting diversity in AI development teams can also help reduce bias and ensure that AI design tools are inclusive and representative of all cultures and communities.
— Data privacy is a critical concern when using AI design tools. These tools often require access to user data, which raises privacy issues
— Designers and AI developers must prioritise user data protection, implementing robust security measures, and complying with privacy regulations such as GDPR and CCPA.
— AI design tools analysing audience demographics, behaviour, and preferences, can suggest design elements that resonate with the intended viewers.
Hyper-targeted design: AI can analyse vast datasets to create designs that cater to highly niche audiences.
— Whether it’s in 3D design, virtual reality, augmented reality, or hyper-targeted design, AI’s role in shaping the future of graphic design is bound to be transformative and exciting.
— Design schools and institutions have recognized the growing importance of AI in the design industry and have adapted their programs accordingly.
— AI is now a fundamental component of design education, and students are exposed to its principles and applications from the early stages of their learning.
— Design curriculum cover a range of topics, including the basics of AI and machine learning, AI-powered design tools and software, and the ethical considerations surrounding AI in design.
— One of the key objectives is to prepare students for the reality of AI-driven design in the professional world.
— Preparing students for AI-driven design involves instilling a mindset of adaptability and continuous learning.
— Design schools are increasingly using AI for administrative tasks, such as managing admissions, optimizing schedules, and personalizing student experiences.
— AI-driven chatbots are used to assist students with inquiries, freeing up administrative staff for more strategic activities.
— Design schools are fostering partnerships with AI companies and industry experts to provide students with real-world exposure to AI applications in design.
— Challenges encompass ethical considerations, necessary ongoing learning and adaptation, and the balance between harnessing human creativity and relying on AI automation.
— Designers must stay updated with the latest developments in AI technology to effectively incorporate these tools into their creative processes.
— This includes understanding the capabilities and limitations of AI, as well as mastering the use of AI-powered software and platforms.
— Could lead to a homogenization of design styles and a loss of the unique, human touch that defines creativity.
— Designers should continue to cultivate their creative thinking, ideation, and artistic expression, using AI as a tool to amplify their capabilities rather than as a substitute for creativity.


A Model for Understanding the Evolving Role of Graphic Designers in the Era of Artificial Intelligence (Excerpts)
— Graphic designers’ comprehension and terminology of the topic often struggle to keep up, resulting in misconceptions, concern, and worried fearmongering about the potential loss of jobs, automation, and deskilling of their discipline.
— Historically, the use of technology can be traced back to ancient Greece, where figures like Daedalus and Heron of Alexandria designed machines capable of writing text, generating sounds, and playing music.
— The 19th century Arts & Crafts movement, for instance, was founded in protest against the displacement of humans by industrialisation.
— Arts & Crafts idealised the innate human creative impulse, craftsmanship, and the meaningful creation of unique, soulful objects.
— Charles Robert Ashbee (1894), later recognized that machines had come to stay and stated, “We do not reject the machine, we welcome it. But we would desire to see it mastered”.
— Contemporary counterparts for regulation and judicious use of technology include initiatives such as Tim Berners-Lee’s #ForTheWeb campaign (Cañares et al., 2018) and, most recently, an open letter (Future of Life Institute, 2023) currently signed by over 27,000 AI researchers advocating for a moratorium on AI development.
— The proliferation of the internet in the 1990s heralded the transition from static print to dynamic digital communication, forcing designers to embrace working with interaction, interfaces, multimedia, animation, and code.
— By the late 2000s, smartphones arrived, bringing with them the need to design for new platform affordances and usage patterns.
— In the 2020s, AI is designated as the next major disruptive technology. Each of these technological advancements has demanded a reskilling of the workforce, necessitating the acquisition of new skills, and embracing novel production and distribution methods.
Deductive design activities: Deduction employs logic, rules, algorithms, guidelines, theories, and norms to yield specific outcomes. Colour theory, principles of composition, typographic treatment, guidelines in old brand books, modern rule-based design systems, and algorithmic-based creative coding are all examples of deductive practices.
Inductive design principles: large datasets make specific observations forming the basis for a model with general (biased) knowledge of the data it is trained on.
— Inductive AI's are adaptable and versatile due to their reliance on decision trees, neural networks, and clustering algorithms.
— Traditional graphic design tasks based on induction include data analysis, gathering inspiration, and trend spotting, among others.
— Abduction complements deduction and induction by creatively inferring design solutions from observations and contextual cues, often described by designers as using their “common sense,” “intuition,” or “gut feeling.” Abduction is currently considered a significant blind spot for AI.
— The placement of abduction is deliberately chosen to reflect graphic design as a fundamental human-driven activity, where humans—with their empathetic and creative abilities—serve as the interface to the surrounding world, encompassing both objectives and application. This model positions humans as the initiating factor in any human-machine collaboration.
— The outcome of any initiated automation is described as “augmentation.” such as general enhancement of tasks, generating new ideas, faster execution, rapid iteration, efficient exploration of solution spaces, more precise insights, pattern recognition in collected data, etc.
— Many modern AI design tools are commercial, proprietary, closed ‘black box’ systems accessible through a basic interface hiding a level of complexity that even their creators may not be able to fully explain. The term ‘black box’ is assigned to (mostly inductive) AI tools characterized by extensive complexity or opacity in their rules, datasets, models, or internal mechanisms, making the underlying rationale behind their outputs difficult to elucidate.
— Often, many simple tools mistakenly labeled as “AI-powered” are merely mundane algorithms that generate their output using pre-made template designs, combinatorics, pre-defined flows, or deterministic rules without any intelligent intervention from the machine.
— Conversely, genuine AI tools are the result of immensely complex and sophisticated computations.
— The new AI/human partnership in graphic design will likely give rise to a wide range of predicates such as “AI-assisted,” “AI-made,” “AI-generated,” and “AI-powered.” These attributions are beneficial for marketing purposes.
— As the collaboration between AI and humans consolidates, it will become implicit to mention that AI has contributed to the design process.
— The power balance between humans and machines is clear: AI works for us, not the other way around. We must control the tool; the tool should never control us.
— The “Future of Jobs Report 2023” (World Economic Forum, 2023) forecasts that the three main areas of reskilling for graphic designers are the ability to work with AI and Big Data, analytical thinking, and creative thinking.
— Design schools need to adapt their curriculum and teaching methods to reflect the increasing use of AI as assistants and inspirational co-creators.
— Strengthening the theoretical and practical aspects of the graphic design discipline is essential to counterbalance amateurishness.
— The ability of humans to blend soft skills such as intuition, empathy, sympathy, and emotional intelligence with their experience and professional expertise is an invaluable factor in the abductive process referred to as “creativity”.

Source: Stig Møller Hansen, ‘A Model for Understanding the Evolving Role of Graphic Designers in the Era of Artificial Intelligence‘, HUB - Journal of Research in Art, Design and Society, 0 (2023)

— AI today has been integrated into a variety of economies, the design industry is no exception. As a result global labor markets are undergoing major transformations.
— How are these changes affecting and will continue to affect designers’ work in the future?
— What skill sets will be needed for designers to begin or continue working in the industry?
— (AI) influences business by creating competitive advantage, new opportunities, expanding the range of customers, connected devices that provide a constant flow of data on functionality, usage, production, and customer needs.
— World Economic Forum (2020) data shows that “by 2025, 85 million jobs may be displaced by a shift in the division of labor between humans and machines, while 97 million new roles may emerge that are more adapted to the new division of labor between humans, machines, and algorithms”.

  1. Architects and designers will be replaced by software applications.
    Sebastian Errazuriz (2019) believes that ninety percent of architects will lose their jobs, if artificial intelligence takes over the design process, since machine learning will allow software applications to synthesize a large volume of projects in a short time, customers will be able to define to an app their intensions, requirements, and budget and get a range of options in seconds. S. Errazuriz (2019) considers that only 1%, maximum 5% of architects will survive, so a tiny elite will continue architecture. In this context he recommends designers and architects to become programmers.
  2. Designers and architects will not be replaced by technologies in the near future.
    In turn, results of a survey of graphic designers "Will" Graphic Designers “be replaced by AI & Robots?” (Will Robots Take My Job?, n.d.) show that there is a very little chance of this profession being replaced, however, the chance of automation in the next 2 decades could be 39%.
  3. AI facilitates architects’ and designers’ workflows by analyzing large amounts of data in a short time and offering solution options.
    Another group of authors (Ervin, 2019; Philips, n.d.; Tailor Brands, 2019; Andersen, 2019) – design thinkers and researchers (Verganti et al., 2020) – believe that AI will transform the design industry, yet these technological advances will not replace human designers. AI will mainly be related to optimization and speed. M. Philips (n.d.) claims that designers working with AI will be able to create designs faster and cheaper due to the increased speed and efficiency it offers.

— Problem-solving, usually performed by designers, is automated into learning loops that think in a radically different way than a designer. They operate without limitations of volume and speed, address complex problems through simple tasks, iterated exponentially (Verganti et al., 2020).
Symbolic AI: programming methods and systems that use symbols, such as letters and numbers, to encode human knowledge, rule-based actions, and defined policies.
— Symbolic AI thinks like a human. Symbolic AI is the most well-known and widespread AI systems applied in manufacturing and production, design, process planning, production control, and diagnosis (Lee et al., 2019).
Neural AI: Relies on an artificial neural network (ANN) or an aggregate of machine learning algorithms enabling computers to learn from data. “Technically, can be classified into three areas: (1) supervised learning, which involves learning from correct answers (labeled data); (2) unsupervised learning, defined as finding knowledge or information when given some raw data (unlabeled data); and (3) reinforcement learning that entails how agents in an environment take action to maximize their rewards” (Lee et al., 2019).
Generative AI: Identifies design intent within design boundaries (parameters and rules), the process may be defined as Generative Design technique” (Monizza et al., 2017). Generative design is an iterative process that uses advanced algorithms to find the best solutions.
Parametric design: An interactive process that allows creating designs based on the input of parameters, such as materials, site constraints, even environmental issues, to test options and to make changes in real time (Rahman, 2020;, n.d.). According to the author (Reddy, 2020), such a tool and process allows artificial intelligence to reduce human effort giving the best results possible by analyzing a large amount of data. AI-driven parametric design allows designers to quickly and easily explore a huge number of alternative directions creating millions of design variations in a small amount of time. The productivity of most designers will increase dramatically (AI and the Future of Design…, 2017).

Can Everyone be a Designer?, Tailor Brands Studio, Design Iconic and Brand Crowd.

— AI logo design sites: possibility to define the industry; for some, to choose keywords and slogans; to choose a type of sign – only text or symbol and text; to choose a coloristic solution;
— Customers have limited options to adjust the selected option – change the distances between letters, lines of text.
— Although there are some positive examples, there is a possibility that the world will be flooded with design solutions of mediocre or questionable quality.
— Only a person with a professional education can develop solutions, including samples, to teach AI, that complies with the principles of “good design” (Rams, 1976),
— Designers will have to plan and manage processes as curators, innovation managers, or art directors.
— Only the designer can define what is meaningful and important, determine when to continue the process and when to stop, approve or reject the solution.
— The demand for designers with traditional design education will decrease in the future. This makes it necessary to consider changes in the design education process and content.

Artefact. (2017). AI and the Future of Design: What will the designer of 2025 look like? Retrieved from ner-of-2025-look-like-b27ad0f6ef3a

Andersen, M. (2019). How Design Schools Are Keeping Up with AI and Machine Learning. Xd, Adobe, Ideas. Retrieved from

Archistar. (n.d.). Parametric Design vs. Generative Design – the Pros and Cons. Retrieved from

Errazuriz, S. (2019). Sebastianstudio. Retrieved from tv/B3jzjj0joCf/

Ervin, J. (2019). Artificial Intelligence & Its Impact on the Design Industry. Just Creative. Retrieved from

European Commission. (2020). Policy. Artificial Intelligence. Retrieved from

Girling, R. (n.d.). AI and the future of design: What will the designer of 2025 look like? Retrieved from

Hansmeyer, M. (2003-2019). Projects. Retrieved from projects

Kulinkovich, S. (2020). Nikolay Ironov. International conference “Design. Experience. Challenges 2020”, October 30, 2020, Riga, Latvia. Retrieved from

Lee, J., Suh, T., Roy, D., Baucus, M. (2019). Emerging Technology and Business Model Innovation: The Case of Artificial Intelligence. Journal of Open Innovation: Technology, Market, and Complexity, 5(3), 44.

Lubell, S. (2018). Will Algorithms Be the New Architects? Dwell. Retrieved from

Monizza, G. L., Raucha, E., Matt, D. T. (2017). Parametric and Generative Design Techniques for Mass-Customization in Building Industry: a Case Study for Glued-Laminated Timber. Procedia CIRP 60, pp. 394. Elsevier. DOI:

Nikolay Ironov. (n.d.). Art Lebedev. Retrieved from

Pandya, J. (2019). How Artificial Intelligence Is Transforming Business Models. Forbes, 7, 10. Retrieved from

Philips, M. (n.d.). The Present and Future of AI in Design (with Infographic). Designers. Retrieved from

Irbite, Andra & Strode, Aina. (2021). ARTIFICIAL INTELLIGENCE VS DESIGNER: THE IMPACT OF ARTIFICIAL INTELLIGENCE ON DESIGN PRACTICE. SOCIETY. INTEGRATION. EDUCATION. Proceedings of the International Scientific Conference. 4. 10.17770/sie2021vol4.6310.

Why graphic designers think generative A.I. needs them as much as they need it (Excerpts)
— Adobe Firefly is one of many new generative artificial intelligence image tools, along with Midjourney, DALL-E, and Stable Diffusion.
— The results are only as good as the human mind prompting the A.I. programs.
— “Advances in AI affecting the world of graphic design are much of the same advances we’re seeing elsewhere,” said Nicola Hamilton, president of the Association of Registered Graphic Designers. “ChatGPT is becoming increasingly capable of doing our writing and planning, while Midjourney and DALL-E are creating pretty advanced artwork when given the right prompts,”
— Pum Lefebure, co-founder & chief creative officer at Washington, D.C.-based agency Design Army, created a campaign with the help of Midjourney for a high-end eyewear retailer Georgetown Optician. “It was a massive undertaking to create. Learning how to prompt the AI still requires an extensive knowledge of image making and a lot of hours,”
— As an image board, or mood board AI can play an important role, Lefebure said. But he added, “It takes a lot of finessing and you really need to train the AI. You need to craft the vocabulary to get the results you want. It’s not a mind reader.”
— Adobe Photoshop’s new AI Generative Fill, “is turning a lot of heads right now,”
— Getty Images is among core creative asset vendors that taking legal action on copyright grounds.
Copyright: Hamilton noted that many of the generative image applications don’t own the artwork they are referencing. “Once that artwork has been generated, who owns it then? Can designers put it out into the world as their own? Can they sell it to a client to use as advertising? It’ll be years before we’ve regulated the ways AI-generated artwork is licensed,
— True artists don’t use Adobe gen AI just to throw a cat into a design because you need a cat,” he said. “There has to be a reason and purpose behind how you use it.” Lefebure (Jake Lefebure, Pum’s husband, and co-founder and CEO of Design Army,)
— “The key use cases we see for generative AI in graphic design fall into inspiration — as a component into a mood board, for example; and composition — as an asset in a workflow to create an output for print or digital,” said Katie Gregorio, senior director of creative cloud marketing at Adobe.
— Sven Travis, associate professor of media and design at the Parsons School of Design, The New School, said while Firefly is one of many gen AI image tools, what distinguishes it is being integrated into the Adobe universe.
—“It will likely make some designers redundant,” Hamilton said. “In the same way that Canva made some designers redundant, or the introduction of computers pushed some folks out of the industry. It’s all the more reason to dabble now, to get acquainted with the technology, and to look for ways we can make it work for us,” she added.
— Many AI experts have said that humans with AI replace humans without it, rather than machines replacing humans.
— “The underlying notion of what it means to be a graphic designer hasn’t changed,” Travis said. “It is about creating effective visual communication. AI can’t tell us when we have achieved effective visual communications.”
— Where designers have been left behind, he said, is when they refuse to embrace new technologies. Travis said.


How AI is Changing the Design Process
OII researcher Maggie Mustaklem
— Pinterest and Instagram. These social media platforms use “everyday AI”, including Natural Language Processing (NLP), machine learning and computer vision.z
— AI is evaluated critically in many contexts, from facial recognition to election misinformation.
— If the platforms designers use for inspiration are the very same ones culpable of well-established biases in other areas, it stands to reason the design process also deserves our attention.

What’s Missing in Digital Negative Space?
— When it comes to thinking about bias in the context of design inspiration, digital negative space is a helpful framework. There are billions of images online, but what don’t we see when we search online? I.E: A search for Dutch design returns sleek contemporary design, not wooden shoes. On the other hand a search for Indian Design returns handcrafted traditional block printed textiles, saris and hand carved furniture. Who gets to be modern in this context, and who gets to influence contemporary design? A fetishised, colonial version of India narrativises what users of social media platforms see, and what they don’t. Dutch designers are renowned and among the most financially successful in the design industry. AI may be unwittingly reinforcing their success while marginalising contemporary Indian designers, relegated to digital negative space.
— Breaking a search down into components that need to be collaged (by a human) may lead to less prescriptive results.
— In the real world, design research operates on compressed timelines, making it a task suited to further automation. But as one participant said, “this is the fun bit.” Designers get a lot out of doing research.
— There are numerous stories emerging of bias in the training data for Large Language Models (LLMs), mirroring existing criticisms of AI tools currently in use. Additionally, LLMs are primarily text-to-image. This requires a professional’s situated, embodied understanding of the prompts they use.


Who and What is Designing Design? (Excerpts)

— Images searched via algorithmic platforms during ideation have aesthetics, values and points of view that can marginalize others. Algorithmic images are ranked through systems that Chandra notes favour “power, privilege, gender, and cool”.
— Even photographs of seemingly innocuous visuals like decorations and recipe inspirations on Pinterest are weighed with a performativity to adhere to rigid gender norms, idealizing hyperfeminine domesticity.
— Endogenous algorithmic systems that distort and polarise images are the systems creatives rely upon for original creative inspiration. As our attention is focused within a narrower sphere, what does this mean for the future of inclusive design practices in creative work?


Research Programme on AI & Work (Excerpts)
— Deep-seated fears about the societal and economic disruptions that AI systems might bring.
— Include the role of AI technologies in the automation of paid and unpaid work, the proliferation of algorithmic management practices and reduced autonomy across organisations, rising inequality, as well as the possibility for social unrest and political backlash.


The AI Dilemma In Graphic Design: Steering Towards Excellence In Typography And Beyond (Excerpts)
— AI is poised not just to generate innovative fonts but to fundamentally revolutionise our text communication, paving the way for a new era of dynamic and interactive typography.
— Vector graphics, defined by Bézier curves, present a more complex challenge for neural encoding due to their algorithmic nature.
— Type designers are increasingly concerned that their specialised skills, including typography, might be overlooked in a landscape filled with AI-aided enthusiasts.
— A positive step forward would be for type-foundries to collaborate, pooling their resources to create a collective AI software model. This cooperative approach would enable them to not only capitalise on AI-driven innovations but also safeguard their unique designs from unauthorised use by others.
— Change is coming, and as designers, it’s not enough to merely accept that change; we must actively steer it, applying our expertise, taste, and judgment.
— It’s crucial that we collectively guide the integration of AI in typography to do more than automate — we must aim to elevate.


Designing with AI: A User Study to Explore the Future Role of AI as a Collaborative Tool in Graphics Design (Excerpts)

— What are the perceptions and concerns of designers regarding the integration of AI into graphic design considering the future of AI-powered tools?
— What are the concerns of designers regarding the ethical implications associated with AI in graphic design?
— It is crucial to recognise the limitations of AI when it comes to creativity and the ability to generate entirely new designs

[42] Mustafa, B. 2023. The Impact of Artificial Intelligence on the Graphic Design Industry. resmilitaris, 13(3), 243–255. Retrieved May 14, 2023

— Despite their capabilities, machines still lack intention and personal goals, requiring human designers to guide and approve designs [47].

[47] Rezk, S. M. 2022. The Role of Artificial Intelligence in Graphic Design. In Proceedings of ACM Applied Arts, 1-12.

Organizations and practitioners ethical considerations: Integrating ethical behavior into AI through the incorporation of pedagogy, moral psychology development, and computer science has been proposed as one approach [53].

[53] Vanhée, L. and Borit, M. 2022. View point: Ethical By Designer - How to Grow Ethical Designers of Artificial Intelligence. Journal of Artificial Intelligence Research, 73, 619-631.

— Significant ethical considerations and fairness implications. This becomes particularly relevant when autonomous systems design themselves, learn, and improve over time [18].

[18] Dhar, V. 2016. The future of artificial intelligence. Big Data, 4:1, 5–9.

— The application of a feminist perspective in AI ethics offers valuable insights into ethical theories, real-world implications, power dynamics, and contextual factors [50].

[50] Siapka. 2022. Towards a Feminist Metaethics of AI. AIES '22: Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society, July 2022, 665–674.

— Adobe Firefly is designed to generate images that are safe to use in commercial settings, leveraging licensed images from Adobe Stock and open-source content. This demonstrates the implementation of AI-generated content in a professional context [1].

[1] Adobe Business Blog. [Online]. Available at:

— A survey was designed to assess designers preferences, attitudes, and opinions regarding AI tools [26].

[26] Gray, C. 2014. "Better User Research Through Surveys." [Online].

— The survey questions were carefully crafted to gather data on the participants’ backgrounds, qualifications, and alignment with the research topic. It also included questions related to their usage of AI, the frequency of AI tool adoption, the current challenges faced, and their future expectations about AI tools in graphic design.
— A participant stated, the sentiment of inevitability surrounding AI’s presence in the design field “I think it’s mandatory and need to get comfortable because it is inevitable and we need to befriend, doesn’t matter if it’s bad or good.”
— “AI doesn’t have any personal opinions, they do not have any reasons for creating except for what the code and the data are been telling them.”
— A participant emphasizes the potential homogeneity that could arise if everyone starts relying solely on AI, stating, “When everybody starts using AI, there will be sameness… people will start valuing exclusivity and will value rare work.”
— Human designers can offer a differentiation factor, producing exclusive and distinctive designs that stand out in a landscape saturated with AIgenerated content
— Designs, crafted by human designers, hold value and appeal in a context where AIgenerated content becomes more prevalent.
— Drawing a parallel to historical skepticism towards new technologies, another participant references the invention of the computer and the skepticism that arose around whether it could
produce art. They state, “So even when the computer was invented, people started saying he is not an artist because he is using the machine.”
— “AI can assist in certain aspects; it lacks the human touch and creativity necessary to imbue designs with genuine emotion.”

Potential for Lazy Design and Ethical Concerns
— “It could make for lazy design for rather than going a pencil sketch some corners are cut, rather AI can join dots, it has some ethical concerns, some managers are concerned about
remote working as there staff is having multiple jobs using AI”. This sentiment raises ethical concerns about the level of craftsmanship and originality in AI-generated designs.
— Necessity for ethical guidelines and education in AI-driven design.

Need for Ethical Guidelines and Education
— “If AI saves your data and reproduces it in some corner of the world, I will not be happy with it, and I think it is immoral.”
— “I think we should have clear guidelines as soon as possible. Before we delve into any danger, dangerous situation”

Urgency for Transparent and Accountable AI
— They desire a clear understanding of how AI operates, where the data originates, and how it is utilized.
— Participants express reservations about AI potentially using or replicating the work of other artists, questioning the fairness of such practices. One participant remarks, “If it taps into other people’s creativity and their capabilities, then it is not fair.”
— Need for recognition and proper attribution,
— “If I use AI to produce something, or something inspired by someone’s design or artwork, so those people needs to get value and credit and so when AI produces my artwork it should also link it back to the person’s just the way blogs uses images and credits to its owner”
— “I am Using AI to produce data I would like to have clear instructions or a clear image of where the data is coming from and how AI is dealing with my data.”
—Participants call for the establishment of ethical guidelines, education on AI ethics, and transparent practices to ensure accountability and mitigate potential negative consequences.
— The integration of AI into the design process necessitates the establishment of clear guidelines and frameworks to address fairness and data privacy concerns [4]. Responsible AI approaches, which prioritize fairness, transparency, and accountability in the implementation of AI methods, have been proposed to address these ethical considerations [4].

[4] Arrieta, A. B., Díaz-Rodríguez, N., Del Ser, J., et al. 2020. Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI. Information Fusion, 58, 82–115.

Designing with AI: A User Study to Explore the Future Role of AI as a Collaborative Tool in Graphics Design. Iram Fatima. Supervisor: Fatima Jonsson. Södertörns University. User Experience and Interactive Media design.


Achieving new limits: Using AI in graphic design
— Companies can now create starting materials before hiring graphic designers to build on their sketches and expand them.


Effectiveness of Artificial Intelligence in Graphic Design (Excerpts)
— AI is beginning to show that not only can he perform tasks faster than humans, but can also think creatively.
— Thanks to AI, machines can do the same tasks that human designers do faster and cheaper.
— The process of design thinking in AI has led to a reduced need for human designers, as machines can now do most of the design work.
— Some computer models have already shown, natural selection can actually outpace the skills of human designers. Natural selection can be so deterministic that it often leads to innovations that some consider evidence of intelligent design (Ra, 2016, p. 128).

Ra, A. (2016). Foundational Falsehoods of Creationism.Durham, North carolina: Pitchstone Publishing.

— One of the aspects that scares some more than others is that artificial intelligence has shown some human-like cognitive abilities, so that machines can relatively think and learn like humans. (Uri Wilensky, 2015, p. 6).

Uri Wilensky, W. R. (2015). AnIntroduction to Agent-Based Modeling: Modeling Natural, Social, and Engineered Complex systems without Netlogo.Cambridge: MIT Press.

— That is, AI systems can see, hear, and feel everything that happens in their surroundings. And these cognitive capabilities work with the help of the Internet of Things and sensors associated with artificial intelligence systems.
— Artificial intelligence systems can analyse and classify existing graphic designs based on their elements and characteristics. It can help identify design trends and analyze the effectiveness of existing designs.
— AI systems can provide feedback on existing graphic designs and make recommendations for improvement. Machine learning techniques can be used to analyse the design and provide guidance to improve it and make it more attractive and effective.
— AI systems can design new and creative fonts. It can generate innovative letterforms and improve the readability and aesthetics of fonts. (vivry, 2023)
— We are witnessing the birth of artificial creativity) (Mould, 2018, p. 125).

Mould, O. (2018). Creativity, Against.London: Verso Books.

— Some graphic design applications that run on AI and machine learning algorithms are as creative as Graphic Designer. However, this risks undermining the profession and creating a second class of "non-professional" designers, particularly in less creative works.
— AI cannot create original artwork on its own. Instead, it relies on predefined templates or designs created by humans. This limits the effectiveness of AI in creating unique and innovative designs.
—For creativity in artificial intelligence, it has become linked to textual or pictorial human input, sometimes that does not necessarily need a real artist or designer!
— One of the most prominent problems is the lack of sufficient and high-quality data to train artificial models, as the use of deep learning and artificial neural networks requires significant training on a wide range of different images and data to achieve the desired result
— "A machine does not have autonomy over the moral level, because even if it happens to confuse and mislead us during its operation, it has no self-will, and remains subject to the goals we set for it." (Ghanasya, 2018)

Ganasia, G. (2018). UNESCO. Retrieved 06 December 2023, from unesco:

— AI can create designs faster and at a lower cost..


How Hollywood writers triumphed over AI – and why it matters

Source: intelligence#:~:text=One%20of%20the%20most%20closely,a%20battle%20over%20human%20creativity.