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“You can see the shift in how companies are answering queries related to social impact,” said Carla A. Harris, senior advisor of Morgan Stanley, during the “Inclusive Capitalism” panel at the 2024 Milken Institute Global Conference.
The panel included Ms. Harris, as well as Troy Duffie, director at Milken Institute; Nisha Biswal, deputy CEO of the US International Development Finance Corporation; Roger Ferguson, former president and CEO of TIAA; and Martin Nesbitt, co-CEO of The Vistria Group. As I listened to the inspiring speakers discuss their philosophies on diverse, and therefore healthier, economic ecosystems, I noticed that parts of the conversation kept coming back to language. “Redefining capitalism,” “communication revolution,” “elevate the conversation,” and “normalize the language,” are just a few of the phrases from the discussion that piqued my interest as a marketing communications professional.
It seems that the way we talk about economic equity has taken center stage over how we accomplish it. To understand why language is central now to the intersection of social impact and capitalism, you must reflect on where we’ve been. As Ms. Harris rightly pointed out, 15 years ago many investors and corporations were hyper focused on measuring environmental impact. Just a few years ago in 2020, the focal point of social impact became diversity. Today, some corporations are opting not to use the terms “diversity” and “DEI” at all, instead moving toward leveraging the term “inclusion” to be all encompassing. In a recent Washington Post article by Taylor Telford and Julian Mark, Atlanta-based employment attorney Marilyn Fish noted that many of her clients, including some Fortune 500 companies, have newly renamed internal diversity-focused programs to put the word “inclusion” at the forefront.
The sometimes-unspoken truth present in this history is that the way we talk about social impact and equity is highly dependent on how we as humans relate to what is happening in our culture of capitalism. As a Time article by Eugene Linden notes, the issue of climate change became politicized in the 1990s. In 2020, our world faced a “racial reckoning” after the murder of George Floyd at the hands of police. Just three years later, Affirmative Action was repealed by the Supreme Court.
Each of these moments in time shifted the cultural consciousness of what good and profitable social impact might look and, importantly, sound like. In each of these moments, our capitalism ecosystem responded in one way or another—even no presence of culturally relevant social impact- and equity-related language is, in fact, a response.
The link between culture and capitalism is very real. We should expect cultural capital and the language we use to bring relevance to economic equity and social impact to shift. This will always be true, as younger generations enter capitalist society and leverage their unique experiences, perspectives, and tactics to combat inequities.
In short, the context around economic equity will evolve and so will the language. It is the underpinning philosophy that creating an inclusive economy is good for everyone, including businesses’ bottom lines, that remains consistent. For example, despite the current anxieties we see cropping up in corporations around diversity-focused language, we know that “an ecosystem that is diverse is much stronger,” noted Mr. Ferguson during the panel. Ms. Harris also went on to say that in capitalism, “we are all competing around innovation, and you need a lot of ideas, perspectives, experiences, and diversity in the room to get to the one that puts you on top.” The same Washington Post article highlights a McKinsey study showing that companies with high racial, ethnic, and gender representation are 39% more likely to financially outperform.
As we near the 2024 general election, many corporate leaders may be holding their breaths—and tongues—for the outcome. One result may evoke a “challenger” response in capitalism, while another may establish a “too-slow-but-steady-progress” economic and legal environment. In either scenario, advancement in equity and inclusion remains beneficial for capitalism.
If we start with those baseline concepts—inclusion is good for capitalism and context will shift language—then our job is simply to understand the shifts and continue to communicate our equity-based values from a place of authenticity and relatability.
After all, “if we made it up, we can fix it,” said Mr. Nesbitt of capitalism and democracy.
By Megan Tuck
Photo by Andre Moura via Pexels
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Whilst the headlines and sites regulated by the Control of Major Accident Hazards Regulations 2015 (COMAH) often focus on major risks and incidents, across the UK, smaller scale leaks causing injury (sometimes devastating long term injury) are common.
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Whilst the headlines and sites regulated by the Control of Major Accident Hazards Regulations 2015 (COMAH) often focus on major risks and incidents, across the UK, smaller scale leaks causing injury (sometimes devastating long term injury) are common.
Whilst the headlines and sites regulated by the Control of Major Accident Hazards Regulations 2015 (COMAH) often focus on major risks and incidents, across the UK, smaller scale leaks causing injury (sometimes devastating long term injury) are common.
The benefits of artificial intelligence for the financial services sector are supposedly massive. But financial leaders do not seem gripped by the same sense of FOMO that many other businesses exhibit regarding the technology, with just 14% having integrated it into their corporate strategy.
Since last year, professionals in the creative sector have been hearing a variety of buzzwords. These include artificial intelligence, Generative AI, open AI, chat GPT, and DALL-E. The introduction of Generative AI has significantly changed workflow and processes in the content industry. In a short period, Generative AI has developed numerous applications for creative professionals, who are quickly embracing it to enhance their work efficiency. Here, we will explore how Generative AI works and how it is impacting the nature of work and use cases in the creative works industry.
Generative AI is a form of AI technology which has been trained using AI algorithms like large language models to produce content, including audio, code, images, text, simulations, and videos based on the prompt it is provided.
Historically, AI was used to analyze information and recommend decisions, and information based on the training AI algorithms have been provided. Generative AI applications like Chat GPT are built on AI technologies and are trained on large amounts of various forms of data to be able to predict and recommend content and information based on the prompt given.
During training, the AI is fed large datasets and adjusts its parameters to minimize errors in its predictions. For example, a text-generating model like GPT-4 is trained on diverse text, learning the statistical properties of language, such as grammar, semantics, and context. Similarly, image-generating models like DALL-E learn to associate textual descriptions with visual elements, enabling them to create images that match given prompts.
Currently, numerous Generative AI tools are available in the market for various use cases. Among them, few are free, and others provide paid services around Generative AI. Some of the prominent Generative AI used by organizations and the public are – Chat-GPT by Open AI, Gemini by Google, Copilot by Microsoft, and DALL-E. The table below lists a few more examples of Generative AI and the type of content it generates as output.
Generative AI ToolType of InputType of OutputGPT-4 (ChatGPT)TextText, code, scripts, email, letters, etc.Microsoft CopilotTextText, code, scripts, email, letters, etc.JasperTextText content, marketing copy, social media posts, blog posts, etc.DALL-E 2TextImages and artMidjourneyTextImages and artNightCafe CreatorTextImages and artMuseNetTextMusicAmper MusicTextMusicJukeboxTextMusicResembleTextVideo
With the advent of Generative AI, the workflow of creative professionals has changed. It impacted the nature of work as professionals now use these AI tools to generate content before drafting a final copy. Generative AI not only helps in providing creative content but also helps in content analysis and content creation process by providing content outline, content strategy, creative graphics, creative content audit suggestions, creative content ideas, summaries, presentations, reports, etc. This not only helps enhance productivity but also creates new artistic expressions. The ease of use and quick availability of these tools further helped in the rapid adoption of Generative AI technology. Below are a few cases of the use of Generative AI in the creative industry.
Generative AI has many use cases across various sectors. A few of them are-
1. Writing and Content Creation – Journalists, marketers, and bestselling authors use AI-powered writing assistants like GPT-4 to write their articles, books, and copy. AI can and does generate news reports, marketing copy, and fictional stories, providing examples of journalist-related AI benefits. One example is The Guardian, which implemented an experimental piece of AI to write opinion pieces. Today, digital media and print media are both flooded with new content that is being AI-generated or refined with AI tools.
2. Visual Graphics and Design Creation– Generative AI like DALL-E and Artbreeder can be used by artists to create novel images and designs. This AI is particularly well suited for concept art, where the exploration of ideas and rapid iteration is key. Graphic designers can use Generative AI to generate logos, layouts, and other visual components of designs. This will not only quicken the design process but can also act as a source of new ideas for the designer. Music video directors could use it to generate initial ideas for a video or even to generate the final video given a song and a desired aesthetic.
3. Music Creation– AI can generate music in many different styles using AI tools like MuseNet and Amper Music. While these are interesting to listen to on their own, they are, more importantly, used by musicians to explore and prompt new ideas. These AI tools generate melodies and harmonies for musicians, who can then arrange, edit, and develop the ideas into complete works. Thus, by collaborating with AI, musicians can explore and break new ground in composition that would be difficult and time-consuming to create by hand.
4. Film and Animation– AI is already generating storyboards, scripts, and even keyframe animations in the film and animation industry. Script analysis and predictions about a film’s likelihood of being a blockbuster or not are some of the decisions that filmmakers are making with the help of tools like ScriptBook. A similar trend is occurring in the animation industry as well. Using AI, traditional animation processes are being automated to free artists up to concentrate on the more creative parts. Memes and GIFs are also being produced with the help of AI tools.
5. Challenges and Mitigations: Generative AI is a very nascent technology and the model it is built on has its limitations in providing accurate quality content. Furthermore, there are several ethical and philosophical challenges as well that have created controversy against its adoption.
These challenges include concerns about:
Exploring Biases: Generative AI might produce biased or unfair content as it learns from data with existing biases.
Copyright Concerns: People wonder who owns AI-generated content and if it violates existing copyrights.
Job Displacement: Some worry that AI might take over human jobs, particularly in creative sectors.
Spreading Misinformation: Generative AI has the potential to generate misleading or untrue content, leading to harm if widely circulated.
To address these issues and enhance the potential of Generative AI, several steps can be taken:
Developing Superior Algorithms: Creating more advanced algorithms that can produce better, more accurate content and reduce biases.
Establishing Rules and Regulations: Reaching a consensus on rules, regulations, and operational guidelines among organizations and governments to ensure ethical use.
Setting Usage Guidelines: Develop clear guidelines for how Generative AI should be used responsibly.
Generative AI has been at the forefront of bringing change to the workflow of the creative industry. It is revolutionizing the nature of creative work, offering new higher opportunities and obstacles. AI intelligently boosts productivity, expands access to creative tools, and opens up new artistic opportunities for art, music, literature, and design production. However, it is critical to mitigate the challenges adequately to ensure that using AI does not decrease artistic creativity but brings out the best of human creativity. The potential of Generative AI lies in realizing the line between its challenges and opportunities in unlocking the age of innovation and creation. With AI, our cultural and artistic works can be more multifaceted and promising than they have ever been before.
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