XXXI: Interview with…Laura Griffin, Strategist
Laura has built her career in strategic communications and PR, collaborating with leading brands. Her focus is on creating and executing clear, effective campaigns.
Laura is a trusted advisor to professionals from founders, boards, and executive teams at all stages. Her curiosity drives her to understand each individual's vision and strengths. This understanding forms the foundation of her approach to creating and designing brands that communicate with purpose and clarity.
Her journey through advertising and brand agencies in Hong Kong, Edinburgh, and Glasgow has been instrumental in shaping her understanding of global and national markets and gaining a practical understanding of diverse communication styles. This experience informs her work, ensuring it's ethical, culturally sensitive and inclusive.
Laura explores AI as part of strategic planning, to support her expertise in social analytics and social listening. This approach helps her stay informed about current trends and anticipate for shifts in the market. Her strategy is focused on creating plans that are not just responsive, but also strategically ahead of the curve, ensuring a proactive stance in a constantly evolving market.
Below, Laura graciously joins us to discuss her views on strategies of self in the era of AI!
https://www.linkedin.com/in/laura-griffin
https://www.instagram.com/lauragriffin.co
www.griffinandco.cc
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The French aspect of the etymology of the English term “strategy” (from the French: stratégie 18c) signifies the “art of a general”. There seem to be immediate connotations that evoke linkages and lines of flight between art and leadership, agency and subordination, dynamics of negotiated teloi. I think, partly, this meaning reflects many people’s association between the term, warfare, competition, indeed violent contestation, perhaps not immediately in the sense of brute brawling, but rather with perspicuity, finesse, and aplomb in outmanoeuvring your opponent or target. How does this reading relate to, if at all, your understanding and work as a strategist?
In my work as a strategist, I see strategy as art and leadership - their connection is vision. It's about creative problem-solving, similar to how an artist uses their canvas. Every decision, like every brushstroke, shapes the outcome. But unlike an artist working alone, strategy is a team effort. It involves collaborating with others and understanding their perspectives.
This ties back to the idea of having the freedom to make choices, but also being mindful of how these choices are influenced by others - like external events, stakeholders or competitors. It's not just about deciding – it's about finding common ground among different views and interests.
When it comes to achieving goals, it often involves navigating through conflicting objectives. It's like trying to find the best path in a maze with multiple exits, each leading to a different outcome. My role is to guide us towards an exit that, while it might not be perfect for everyone, works well for the overall mission.
As for competition, it's not about overpowering others, but about outsmarting them. In today's world, this means being more thoughtful and strategic, not more forceful. It's like playing chess – winning by thinking several moves ahead.
Our discussions about generative AI have opened new perspectives on what it means to be a strategist today. It's an exciting - yet challenging time, as we navigate new technologies and changing expectations in brand communication and marketing.
In essence, my approach to strategy is about being creative, collaborative and thoughtful. It's about understanding that while the game may change, the need for smart, effective strategies remains constant.
Another tacit concept inherent to the etymology of the term brings together, perhaps, the art of the general - here in the sense of a general public - the multitude and that which is spread. How does strategy drive, draw out/forth and move the interest and desire of the public?
Strategy plays a defining role in shaping public interest and desire. It provides a framework that allows us to channel messages, ideas and narratives in ways that resonate with the public. Effective strategists are skilled in using different tools and techniques to not only capture the attention of their audience, but also to drive action.
A key aspect of this is understanding the audience - their needs, preferences, motivations and behaviours. Through this understanding, we can craft messages and create experiences that not only speak to them, but also engages with them on a deeper level. The art of strategy allows us to draw out the underlying desires of the public by tapping into their existing interests and values.
Driving the interest of the public, often involves creating narratives or experiences that resonate with their self-image or aspirations. For instance, in the context of a marketing strategy, we often see how brands find purpose by aligning their messaging with the lifestyle or values of their target audience and nudging their desire for the product or service.
How we “move” the public is perhaps the most challenging aspect. It's not just about sparking interest, but influencing behaviour or even changing perceptions. This is where strategy needs to be innovative, persuasive and resilient. By creating a compelling narrative, providing clear calls to action, and maintaining a consistent message, strategy can effectively move the public to think or ideally behave in certain ways.
So, strategy can serve as a bridge between an organisation or individual and the public. It provides the blueprint for how we can drive, draw out, and move the public's interest and desire, ultimately achieving our goals while serving the needs and aspirations of our audience.
In the function of AI, it’s now becoming a tool that can quickly test ideologies and help conduct sprints to build out audience personas fast and quickly to validate our hypothesis about what those desires may be, and build out a roadmap to action at an alarmingly fast rate.
I think for many, advertising, branding, public relations, and strategy evoke connotations of anti-ethics, guile, ruthlessness, and the ‘evil genius’ of an Edward Bernays outlined in Adam Curtis’ ‘The Century of the Self’. What are your views about him, the history of your industry, and how or if it has changed in your experience?
As a social media strategist in advertising and branding, I view Edward Bernays as a complex figure. His pioneering use of psychological principles in public relations and advertising was groundbreaking, yet his methods often strayed into manipulation. However, it's important to contextualise his work within the era he operated in. Today, many of his tactics would be considered unethical, but they have also shaped the evolution of our industry.
In the history of advertising and particularly in social media, we've seen a spectrum of practices, ranging from triggering or manipulative strategies to more ethical and transparent approaches. My experience in social media advertising so far, has shown me that the industry is increasingly moving towards authenticity and ethical communication. Consumers are more hyper-aware and critical; they value honesty and seek genuine engagement from brands.
The shift in the industry is also influenced by stricter regulations and a greater public demand for responsible advertising. As a strategist, my focus is on creating content that resonates with the audience on a meaningful level, rather than just pushing for sales. It's about building trust and a sense of community around a brand and being transparent in our messaging.
Reflecting on Adam Curtis' The Century of the Self, it's clear it paints a critical picture of Bernays and the early days of our industry. While it's an important reminder of the potential for ethical missteps, it doesn't entirely represent the current landscape of advertising and branding, especially in the realm of social media. The industry today, from my perspective, prioritises long-term relationships with consumers and upholds values of integrity and social responsibility.
So for me, the advertising and branding industry, particularly in social media, has evolved significantly since the times of Edward Bernays. We are now more focused on ethical practices, transparency and creating genuine connections with our audience, which is essential for sustainable and responsible growth in the field.
I don’t know if you’d agree, but I think to many, our tenure in late capitalism is like betting on a derby in which only the Four Horsemen are running, with the only vig against the only superfecta being life itself. Ours is a milieu of malapropism and malady, de-intensified intensity, factionalist instability, socioeconomic upheavals, war, famine, plague and heat death. While I’ll get into these in more depth, I just want to lay out several statements that feature the term strategy. In as long or short an answer that feels right to you, I invite you to respond to the following:
Strategies of/against Accident
Strategies of/against Probability
Strategies of Manufacturing an Audience
Strategies of Affordable Luxury
Strategies of Cohesion
Strategies of/against Automation
The trend of affordable luxury is becoming more important, especially with the ongoing rise in living costs. This idea is about making products or experiences that feel luxurious—like they're really high quality, unique, and special—but at prices that aren't so steep. It's making the luxury market open to more people, finding a good middle ground between something that's really nice and something that's affordable.
Take the Muller Corner ad, for example. It's simple but it gets the point across well. The ads are minimal but they still manage to look fancy. Muller isn't super expensive, but the way it's shown makes it seem like it's not just your average yoghurt. The ad is low-key but classy, making it seem like the luxury of the product is in how good it tastes and how much you enjoy it. This smart way of showing the product meets people's desire for something fancy, but without the big price tag.
In an episode of 'Emily in Paris', there's a moment where Emily picks a gold Eiffel Tower bag charm during a meeting with a French fashion designer, who then finds it tacky and calls her "basic". This scene shows that luxury brands are trying to reach more people by adding cheaper items to their lines. It shows that even small things can make people feel like they're part of a special group. It's about making everyone feel welcome and building loyalty to the brand.
Affordable luxury is changing what luxury means. It's not just about being exclusive anymore; it's about matching up with what people believe in. Social media is a big part of this change, making luxury seem more everyday and focused on important stuff like being ethical and caring for the environment. Why is this a big deal? Because people today are different. They don't just buy things; they buy into what the brand stands for. They want luxury that fits into their everyday life, that's about both being top-notch and practical. This is the new kind of luxury—it shows how people's attitudes are changing, blending luxury with doing the right thing.
Let’s talk about brands. During our conversation, we spoke about brands and transcendence as an example of how brands bring together a type of transcendence-beyond-the-status-of-product, that ineffable religiosity that can coagulate and congeal around a product, and its identifiability. First, does this freak you out in any way, or is it rather useful and pragmatic to you? Second, and I’m jumping the gun a little here, in what ways can or cannot AI achieve similar affects, in your view?
Building a real connection with customers goes beyond selling products or services. It's about connecting with them personally. When brands do this well, they're not just making sales; they become part of who we are and our stories. This is really powerful. Look at how certain art pieces, like Andy Warhol's 'Campbell’s Soup Can' or Tracey Emin's 'Bed', turn everyday items like Absolut Vodka or Marlboro into cultural symbols and memories.
AI has the potential to create similar impacts as brands, but it has its limits. AI can help enhance these effects. For example, AI-driven personal suggestions and content can make the relationship between consumers and brands stronger. But, it's important to remember that AI cannot replicate the same genuine, emotional bond that comes from human branding efforts.
I think the best way to use AI in branding is to see it as an assistant, not a replacement for human creativity and insight. AI is great for testing out ideas and exploring new concepts, but its true value comes in inspiring human creativity. By taking care of the complex data and repetitive tasks, it frees us up to think creatively and solve problems. This teamwork between AI and human creativity doesn't just make us better; it transforms us, paving the way for new ideas and solutions that were once out of reach.
We spoke a lot about AI. Since Jodorowsky’s Tron dropped, I’ve watched, listened, and read as broad a swathe of the discourse as possible. To me, the rhetoric, morality, alarmism, so-called ‘humanism’, and what the cohesion of these forces may or may not allow or portend, with or without AI, is, to me, sublime in the old sense. As such, it feels also revelatory to see how AI has drawn out investment and interest in the elision of value and labor, difficulty and expertise, struggle and acquisition. I feel there are three very broad categories when it comes to the aforesaid discourse: 1) AI as threat, 2) AI as tool, and 3) AI as fad. We spoke about AI as a tool of strategic visualization. Could you speak about how that occurs and what that looks and feels like for you?
In my recent work, I've been looking at how tools like Midjourney are being used by companies, for example, BMW, to include AI-generated images in their adverts and social media. Platforms like Pinterest Studio are also starting to use AI to help with creating quick product mock-ups.
However, using AI in this way does bring up some big issues. One major problem is the risk of making content that feels generic and doesn't show what makes a brand special. In a time when having a distinct brand identity is crucial for standing out from the competition, this is a big concern.
Another issue is about trust and being real in how brands talk to their audience. Even when it's made clear that content has been created by AI, like with AI influencers such as ‘Your Sis Billie’ from Meta, there's still confusion. A lot of people can't tell these AI creations from the real thing, despite the labels.
The incident where a photo related to Kate Middleton was edited with AI brings up another point. It shows us how easy it is to blur the lines between real and fake, leading to questions about what’s genuine. This kind of situation can make people doubt what they see, affecting how they see a brand or a public figure.
We spoke about strategy in a dualistic way, I think. You put it succinctly: storytelling heart, commercial head. What is your strategy for making them cohere in your life and praxis?
We spoke about how strategy has two key aspects: the emotional power of storytelling and the logical approach of commercial strategy. In my work, I see storytelling as both a creative art and a science. There's a common misconception in advertising and communications that calling oneself a 'storyteller' is somewhat of a joke or implies exaggeration. However, in reality, effective storytelling demands a great deal of creativity, deep insight and articulate expression to make the narratives both compelling and clear.
For example, this is where the 'beermat brief' concept comes in. It's simple: if you can't fit your creative idea or brief on a beer mat in a few words, it's probably too complicated. This is a way to check if your ideas are clear and straightforward. When I consider stories, I prefer to resonate with people on some kind of emotional level. On the business side, which usually deals more with clear-cut thinking, I try to use the same creative energy found in storytelling. It's not just about fitting stories to business goals; it's about reshaping those goals to fit the story in a way that's clear and compelling.
My approach mixes emotion with logic. I believe even the most logical strategies can be emotional, and emotional stories can be logical. It's about more than just putting heart and head together; it's about rethinking their connection. The result is a strategy that's emotionally engaging and commercially smart. For me, real innovation in branding isn't just about balancing storytelling with commercial strategy, but rethinking how they can work together to create a clear and effective proposition.
Sometimes it seems to me that a brand can become a taint, regardless of whether or not that brand ascends or descends over time or suddenly. How can associations between brands and art effect strategy, especially in our era of AI normalization?
For brands, choosing to associate with a particular art style can initially seem like a smart move to enhance their image and build an audience. However, as AI technology makes replicating and popularising these artistic styles easier and easier, brands face the challenge of their chosen art losing its uniqueness and becoming part of creative monotony.
Artists, on the other hand, encounter a different set of challenges in this AI-dominated landscape. They create art with specific intentions or creative vision, but AI's widespread reach can lead to their work being associated with brands or messages that don't match their original vision. This can dilute the artist's message and potentially compromise their artistic integrity.
For example, Wes Anderson's signature style, characterised by its colourful symmetry and meticulous attention to detail, has been rapidly and widely reproduced by AI-driven tools across social media. Brands that initially sought to align with his unique aesthetic might find themselves in a sea of similar associations.
Both brands and artists, therefore, need to navigate this new territory with care. Brands should think beyond the immediate appeal of an art style and consider how it might evolve, especially in a world where AI can quickly saturate the market with similar aesthetics. Artists, meanwhile, need to be more proactive in controlling how and where their work is used, ensuring that it stays true to their vision.
In short, in a world where AI is everywhere, it’s important for both brands and artists to think about the long-term effects of their creative choices. They need to find a balance between following trends and keeping their work authentic and meaningful.
It might be odd to say, but I often think about how much Caesar's escape and victory in Gaul came down to luck and improvisation despite the seeming inexhaustibility of the resource-might of the Roman Empire. I say that to say that as a strategist, it seems to me that a chief concern of any campaign is stock - figurative stock like how much stock one places in success, literal stock like how much resources one has in terms of capital and personnel at their disposal at any given time, accidents of chaos notwithstanding. This seems to me a negative dialectic where possibility is measured against the limits of feasibility. But what happens to strategy when money is no object in determining what’s possible as an experience?
When financial constraints are not a factor, brand strategy shifts from managing budgets to encouraging creativity and the pursuit of innovative projects. This change allows brands to craft experiences that are both memorable and impactful. For example, the marketing campaign for the Barbie movie, which had a generous budget of £150 million, resulted in £1 billion in box office revenue. This illustrates how financial freedom can empower brands to explore ambitious ideas and form partnerships.
However, even when financial restrictions are lifted, brands need to maintain a clear and focused strategy that aligns with their core values and objectives. In such an environment, brands have the opportunity to lead cultural shifts or make meaningful contributions to society. This can build deeper connections with audiences, similar to the impact of Dove’s 'Real Beauty' campaign, which moved beyond traditional advertising to engage with communities in a significant manner.
One of the most interesting things you touched on in our conversation is the behavioral frameworks of strategy/strategy as a behavioural framework. Two questions: 1) how do strategies of behaviour work to “enable” and “nudge”, to use your terms? 2) How do strategies succeed or fail to use AI to develop behaviour?
When we talk about behavioural strategies through 'enabling' and 'nudging', we're really talking about setting the stage for desired behaviours. 'Enabling' means setting up an environment with all the necessary tools, resources and information. It's about making it possible for people to take the actions they need to.
'Nudging' refers to gently guiding people's choices in a certain direction, making some options more attractive or easier to choose without forcing them. This approach aims to influence decisions subtly, encouraging more of the desired choices.
Bringing AI into this conversation changes the game. AI systems need large amounts of data and require careful planning, thorough research and precise implementation. The success of AI in influencing behaviour depends on how relevant and up-to-date its training data is and if its outcomes align with the strategic objectives.
For example, an AI using old or biased data might not be helpful. On the other hand, an AI with the right preparation can analyse huge amounts of data, offering insights and efficiencies we can’t achieve on our own. So, there needs to be a clear connection between what the AI can do and what the strategy aims to achieve.
It might seem an aporia to think about ‘strategy’, with its connotations of precision and measure, in the same thought occupied by experimentation, with its connotations of the unforeseen in play. How do the two interact and/or co-exist for you?
Strategy and experimentation might seem at odds initially. Strategy suggests a detailed, planned method, focusing on data, insights and objectives to provide direction. On the other hand, experimentation is about embracing uncertainty and exploring new ideas. Yet, these two are not just compatible; they are essential for innovative breakthroughs.
Consider strategy as a detailed plan. It is informed by data, insights, and specific objectives, providing direction and stability. Yet, a plan alone doesn’t lead to discoveries. This is where experimentation becomes valuable. It introduces a process filled with creativity, risks, and the exploration of new ideas.
Yet, these concepts are not only compatible; they're necessary for innovation. Strategy offers a foundation, setting boundaries and goals. Experimentation, within these strategic boundaries, allows for exploring new approaches and ideas. It's this mix of planning and exploring that drives innovation. Experimentation feeds into strategy, refining it with new insights. This creates a cycle of creative growth and adaptation.
In my view, strategy provides stability and direction, while experimentation pushes us to explore new areas. Together, they help tackle complex challenges by maintaining a balance between certainty and the willingness to explore.
In relation to ideas about opensource, I was looking over my notes and came across this sentence: “nobody can own the prompt”. What do you think are the best strategies for transparency when it comes to AI?
Transparency in AI, especially with open source, can be improved through several straightforward strategies. First, adopting open-source platforms can help. This approach encourages collaboration and peer review, making it easier to spot biases or errors in AI systems.
Second, detailed documentation is essential. It should clearly explain how AI systems are developed, the algorithms used, the sources of data, and their limitations. This kind of transparency builds trust by allowing users to understand and evaluate AI systems more effectively.
Finally, focusing on ethical design and making AI systems understandable is important. AI should be developed ethically, respecting fairness and privacy. Also, making it easier for people to understand how AI makes decisions helps in gaining their trust and acceptance.
Overall, these strategies can help make AI more transparent. Open source, thorough documentation, and a focus on ethics and understandability not only enhance collaboration and accountability but also help in gaining public trust in AI.
Consistent but still similar; personalised prompts; problems of ownership of what the AI pulls from’ creative direction/art curation to get a cohesive look and feel - Much of our conversation centered around the idea of ‘strategies of cohesion’ with AI - the range of prompts across platforms, but also the mercurial range of what a prompt and its variations (re)produces. In this way, difference and variation would seemingly make it very difficult to claim ownership of AI (re)productions. What are your views and strategies when it comes to AI and cohesion?
When we talk about AI and keeping things consistent, we're looking at AI as a tool that tries to put together a story from bits and pieces of information. Imagine it like doing a puzzle where some pieces are missing. The AI tries to fill in those missing parts with what it knows, aiming to keep the story flowing smoothly.
However, sometimes the AI's guesses don't quite match up, which can throw off the flow or make things less consistent. That's why our approach to making AI more consistent involves constantly updating and teaching it with a wide range of data. This helps the AI know more and do a better job of filling in those gaps, leading to a better experience for users.
Personalisation is also key. We need to train the AI to understand and adjust to specific needs while keeping the story consistent. It's like teaching your AI to be a good chat buddy who knows a lot about you but can also talk about a wide range of topics.
Now, when it comes to owning what AI creates, it's a bit complicated. AI puts together answers based on a huge amount of data it's been trained on. You can own the questions you ask (the prompts), but the answers (outputs) vary a lot. This gets even trickier because AI often works from data that's openly available.
So, our strategy is about getting to grips with these challenges. We aim to constantly improve how the AI understands things and refine our questions to get the answers we're looking for, all while considering individual needs. At the same time, we're navigating through the tricky issue of who owns the AI's creations. We aim for transparency and giving credit where it's due, moving forward in this complex field with clear thinking and innovative ideas.
Even when it’s neither, I think a lot of people might find AI generated images to be a bit too commercial, or not as weird and dark. Which brings up the salient question of what makes it ‘good’, which seems, in the current instance, to require a human to make decisions. The play between variance and consistency brings to mind assumptions and criticisms of ease such as those confidently, if not smugly, professed and demonstrated by Jack White in It Might Get Loud. In view of his proclamation - that “the death of creativity is the ease of use” - you mentioned creating prompts that (re)produce one’s imaginings accurately - which is in some ways fantastically paradoxical - and how difficult this is proving. It seems to me there is still much in the way of surprise, accident, and error when it comes to AI-human interfacing. What have been your strategies guiding your own AI experiments, and what have been your results?
When working with AI and humans together, reminds me of a great quote from James Manyika, who is Google’s Senior Vice President of research, technology, and society. He said, “AI and art are not at odds. AI doesn’t replace human creativity. It enhances, enables, and liberates it.”
This really sums up what I believe and try to achieve in my projects. Setting some limits on what the AI can do, and not making everything too easy, helps stir up creativity. The AI throws out lots of ideas, and then it's up to humans to take those ideas and turn them into something amazing.
It's like having a dance between AI and humans. The AI can produce countless steps and movements, but it takes a human to put soul into the dance. By working together and learning from each other, we can create something that neither could do alone.
James Manyika's words echo the belief that AI is here to amplify what we humans can do. It's not about AI taking over, but rather about how it can help us to unleash our creativity in new and exciting ways.
It seems that part of the alarm and wonder in assumptions concerning AI is that it can do far more than it actually does; that its (over)promise has somehow brought the far future to the shaky present. But for some, as a tool, AI is, perhaps more than finds representation in the Commons, archaeological in nature. It’s a tool of going back and re-discovery. In what ways is this true for you?
I find AI fascinating, especially from an art perspective. My background in fine art, particularly in creating physical collages and mixed-media artworks, has always been about combining different elements to create something new and sometimes contrasting.
AI feels like an extension of this process. It allows me to blend past inspirations with current ideas, treating each AI-generated prompt as a piece of collage, adding depth and texture to the artwork.
Thinking of AI as a sketchbook is a perfect analogy. Just as a sketchbook captures the evolution of an artist's ideas, AI enables the exploration and development of thoughts in a fluid manner. Each prompt acts like a sketch, laying the groundwork for a larger concept.
So, while AI might seem focused on the future, for me, it's a way to reconnect with the history of art and my personal journey through it. It represents a digital merging of the past, present, and future, creating a unique space for artistic exploration.
Another sentence I found in my notes reads: “look and feel as a consequence of a personal strategy”. It makes me think of our discussion of cohesion and its reliance on sequence and a consistent syntax, how the possibility of repetition relies on the precision of input commands. What is your personal strategy in using AI to educe as much cohesion in your process as possible?
To ensure a cohesive process with AI, my strategy revolves around three key actions: maintaining consistency, making adjustments as necessary, and perpetually seeking improvement.
First, it's about consistency - making sure the AI receives clear, consistent data to learn from. This is like how we need clear instructions to do a job right.
Second, being ready to adapt is important because things often change unexpectedly. The good thing about AI is its ability to adjust quickly to these changes. In my use of AI can adapt by continuously updating it with new information or changes in the environment.
In the end, looking for improvements means always checking how the AI is performing and finding ways to make it do things better. This ensures that our AI doesn’t just repeat tasks but gets better at them over time.
I’d say that my strategy is about keeping a consistent input, being ready to change when needed and always look for ways to improve. This way, our AI isn't just copying processes but gets better at helping us more and more as time goes on.
Is the future of AI efficacy a matter of cohesion, repetition, and reproducibility?
The future success of AI comes down to how well it can work together, learn from experience and give consistent results. However, that's not the whole picture. We need AI to keep up with the fast changes in consumer behaviour and technology. This means it should be able to change and improve over time, and it must work in a way that's safe and fair for everyone.
So I’d say yes, making sure all parts of AI are working smoothly together, learning from doing things over and over and being able to trust it to give the same results is key. But equally, it needs to be able to adapt, and we need to be sure it's being used in a way that's good for all users.
It was interesting to hear you speak about your experiments with AI portraiture and, specifically, what the AI chose to focus on as, paradoxically, a particular aspect of diversity. What are your views on the issues and debates surrounding AI interpreting distinctly human phenomena like ethnicity and inclusivity?
Using AI to help understand things like ethnicity and inclusivity comes with its ups and downs. AI can create pictures or models that show a wide range of people. This is a good step towards showing everyone’s unique look and background. But, we also need to be careful about how we use this technology.
Take Levi's, for example. They decided to use AI-made models through a partnership with Lalaland.ai to show more diversity in their fashion lines. The idea was to use these digital models to represent a wide variety of people. However, some Black models weren’t happy with this. They said using AI models instead of real people was a step back. They want brands to hire real models from all backgrounds.
From my point of view, AI has two sides. It can help fight bias by using a lot of different data to make something fair for everyone. This could make it easier for all kinds of people to see themselves in ads or media.
But, there's a big worry that AI might not get it right. It could oversimplify or get wrong the very things that make us unique. If we’re not careful, AI could keep showing the same old stereotypes instead of challenging them.
In my opinion, while AI has a lot of promise for making things more inclusive and diverse, we need to be smart about how we use it. The Levi’s example shows us that it’s important to keep things real and respect everyone’s identity. We need to make sure AI helps us show the real world, with real people, in all their diversity.
You used a fantastic phrase: “spectrum of cohesion”. What does this idea mean to you and how does it relate to current AI efficacy?
The 'spectrum of cohesion' is my concept of describing AI's strengths and weaknesses. At one end of the spectrum, AI succeeds when it rapidly processes vast amounts of data, identifies patterns and makes predictions with remarkable speed and accuracy.
For example, Devin AI demonstrates this by autonomously performing software engineering tasks, such as coding and debugging, efficiency in specific tasks. It can independently plan and solve problems, adjusting its approach based on user feedback.
On the opposite side, AI struggles with understanding human emotions, complex life experiences, and creativity. These areas are difficult for AI because they are not quantifiable, or consistent and are shaped by unique human perspectives and experiences.
This range shows us that AI has limits. It's a powerful tool for specific tasks but cannot replace the depth of human understanding or judgment. AI can act like an everyday assistant, but it does not replace the unique insights humans provide in interpreting complex emotional and experiential data.
For the third position of the the AI apathetes, I think a potential source of their ambivalent indifference when it comes to AI is how unimaginatively its applications have been heretofore - applications that have often been both gazetted and lampooned as both revolutionary and ridiculous. The Metaverse fanfare over the provision of virtual legs, or the blandness of a VR hotel, come to mind. AI apathetes might think of these as tepid escapes from intense conglomerate crises that offer little succor and even less distraction. What, if anything, does the flop of the Metaverse indicate in terms of current corporate strategies of AI, in your view?
Your observation is spot-on. The response to AI, particularly from AI sceptics, is largely due to the lack of imaginative applications. The lukewarm reception of the Metaverse, in my opinion, is more a reflection of the way corporations are employing AI, rather than the potential of AI itself. Many firms are employing AI for flashy but shallow experiences, which fail to meet deeper human needs for connection or usefulness.
Now, looking at the Birkin NFT concept we discussed earlier, it offers a different approach. This idea amalgamates AI with a domain of human interest - ownership and value in luxury digital assets, forging a meaningful link between the virtual and tangible worlds. This type of application can make AI more engaging and valuable for users.
The key takeaway for brands should be to focus on aligning AI strategies with human needs and interests, rather than just the novelty of technology. Such an approach would build greater interest, acceptance, and enthusiasm for AI technologies, ensuring that they're viewed as more than just gimmicks.
Since reading Helen Hester’s Beyond Explicit, I’ve been thinking a lot about intensity in various ways. When it comes to AI, I’m fascinated by its relationship with visuality, visual and popular culture, and the imagistic, simulacral nature of Content. I wonder if our intensification of visuality has de-intensified our capacity for image-affects, that in view of all the maps we have of the territory-out-there - bespoke or deep fried - we don’t really care about the map, the territory it simultaneously and simulacrally promises and produces, or our own apathy toward either. What are your views on strategies to engender and maintain the intensity of image-affect in a world cocooned by, lost within, and re-presented through Content? What strategies do you find interesting in maintaining “the frenzy of the visual”?
Our digital world bombards us with images, challenging us to maintain a genuine connection to what we see. Here's how we can keep our engagement with visuals meaningful and impactful:
First, interaction is key. Instead of passively consuming images, we should engage with them—asking questions, seeking meanings, and letting them evoke emotions. AI can play a role here by prompting us to explore these depths, making images resonate more profoundly with us.
Second, make it personal. The impact of an image can change dramatically depending on who views it and in what context. By ensuring that the visuals we encounter are relevant to our individual tastes and current state of mind, we can strengthen our emotional response to them.
Third, re-introduce scarcity. In an age where everything is available instantly, the anticipation and excitement that comes with waiting have diminished. By making certain visuals more exclusive and creating narratives around them, we turn viewing into a more engaging experience, reigniting the spark that makes visuals thrilling.
Ultimately, the goal isn't just about enhancing the visual experience but ensuring it holds deeper significance for us. It's not solely the image's power but the personal and emotional connections we establish with it that preserve the vibrancy of our visual world.
You said that AI will always require a measure of study. If you were general for a campaign wherein which money was no object, what would you study pursuant to AI?
Absolutely, I strongly believe that AI continues to be a field that demands proper examination in its impact, study and understanding, given its evolving nature. Now, if resources weren't an issue, I would focus on two main areas.
Firstly, the ethics of AI. I believe understanding how AI impacts society and ensuring AI systems are fair, accountable and transparent is fundamental. It's imperative that AI decisions reflect our collective moral compass, steering clear of any bias or prejudice.
Secondly, I would dedicate efforts to the explainability or interpretability of AI. Simply having an AI make decisions is not sufficient; it's fundamental we can understand why it's making that decision. Making AI’s thought process accessible would build trust in these technologies and enable us to refine and enhance them with greater precision.
This is about developing AI systems that are not just smart but are also in ethical agreement with our values and transparent in how they make decisions. This approach would lay a strong foundation for any generative AI-related campaign, ensuring that we're driving positive impact while minimising potential risks
How do you think AI will influence strategies of self in the next five years?
AI is already quickly becoming part of our everyday life. We've already seen the beginnings of this with smart assistants like Alexa, which manage tasks such as checking our calendar and updating us on the weather.
However, the future promises to take this a step further. The next wave of AI could understand our personal objectives and provide automated tailored advice. This goes beyond simple task management to a more nuanced understanding of our preferences and needs.
As this technology develops, it presents an exciting chance for brands to deepen their engagement with consumers. Instead of sending the same general message to everyone, they can use AI to make their messages and offers really fit what we like and need. Imagine a brand that not only knows your shopping habits but can also sense your mood and recommend products or services that meet your current emotional state or aspirations.
This progression means brands could communicate with us in a way that feels much more personal and relevant. It’s about shifting from transactional interactions to ones that are truly shaped around our individual preferences and life situations, enhancing our daily routines and emotional well-being with a level of personalisation we’re just beginning to explore.
How do you see AI altering the way we communicate and share information?
AI is already changing how we talk and share information every day. Many people are still figuring out how to integrate it into their daily lives because there’s not much clear guidance on how to use AI effectively.
For example, AI is becoming key in social media and online content we experience everday, especially with the growing demand for generative AI tools, such as visualisation tools. An example of this trend is Pinterest's new product feature called ‘Creative Studio’, where users can rapidly generate professional creative product shots using their in-house AI technology.
According to a new report from European law enforcement group, Europol, we have all the reasons in the world to be cautious. “Experts estimate that as much as 90% of online content may be synthetically generated by 2026,” the report warned, noting that synthetic media “refers to media generated or manipulated using artificial intelligence.
This could lead to a lot of content feeling the same, because AI uses large data sets to create stuff, which might end up repeating the same ideas and styles. This means we could hear less from unique and different voices online. While AI can make content creation faster and more innovative, it's important to keep a balance so that we don't lose the diversity of human creativity.
How do you think AI will influence strategies and revisions of value?
From my perspective, AI's impact on strategy and value revisions is substantial. AI is set to dramatically change how we approach strategy and assess value.
Firstly, AI is excellent for generating ideas and analysing large volumes of data, providing insights that might otherwise be missed. Though it sometimes points out what experts already know, its capacity to process complex datasets quickly is a major benefit in today's data-centric world.
Regarding strategy, as I mentioned earlier - one of the big benefits of AI is how it handles data. It can spot trends and insights that we might miss, especially when dealing with lots of information. This ability is incredibly useful today since we rely so much on data to make decisions.
When it comes to updating what we value, AI can help us understand what people really want. This means we can adjust more effectively. It can also show us which processes are working well and which ones might need some changes or automation.
So, while AI brings many benefits to planning and assessing value, it's important to use it wisely. We need to balance the insights AI provides with human judgment to make the most of it.
I overheard a Zoom meeting my officemate was having in Accra. One participant said as a joke “the next conference will be held on Tik Tok”. There was a mix of badly hidden alarm and sublimated incredulity in the responses. How do you think AI will influence strategies of communication and strategies of transposition/transliteration of information?
Using TikTok for professional events like conferences might sound a bit out there, but consider this: 72% of its users are open to engaging with live events on the platform. TikTok Live isn't all that different from hosting a live webinar. Both offers a platform for real-time engagement with audiences. This shows there's a huge audience potentially interested in such content. Imagine watching a conference live on TikTok – it's not that far-fetched to think brands could use this to reach their audiences more effectively.
AI is already playing a big role in changing how we talk to each other and share information. It's good at understanding what people like and need, which helps in making sure the content we share catches their interest. By using generative AI, we're able to send out messages that get through to people, encouraging a deeper level of engagement.
The more we use AI, the more we see how it can make our ways of sharing and communicating better. AI promises to make our communication strategies not just smarter but also more personal and meaningful. We're heading towards a future where our digital interactions are made just for us, making it easier to understand and connect with others. This isn't just about making things faster; it's about making our connections stronger and more meaningful with the help of AI.
