AI

At our recent ‘Navigating AI Together’ roundtable, we delved into the critical issue of biases within AI and how we can look to overcome the in-built bias and use AI as a tool to foster inclusion and authentic representation.

We were delighted to welcome Ali Fisher, a seasoned expert in fostering sustainable, diverse, equitable, and purpose-driven business practices. With a background including leadership at Unilever and the Dove Self-Esteem Project, Ali brought a wealth of knowledge and experience in the realm of DE&I. Her invaluable insights provided fresh perspectives on navigating AI’s impact on communications.

Unravelling bias in AI

Generative AI offers amazing opportunities for communicators, but its power comes with a challenge: inherent biases. Generative AI has been trained on human-created content, and so has inherited deep-seated bias built in. This bias can, and often does, unintentionally permeate AI-generated content, reinforcing stereotypes and misconceptions.

It’s been well documented and discussed over the last year that generative AI takes bias and stereotyping from bad to worse – with Bloomberg publishing headlines like ‘Humans are biased, generative AI is even worse’. This bias is of course very worrying when we’re also seeing reports that 73% of users globally already say they trust content created by generative AI.

But let’s go back a step. While generative AI may be biased due to the training data that feeds it, what about the conditions under which the AI tools themselves are developed?

The lack of diversity within the tech industry adds complexity. The gender disparity is evident, with only 22% of the UK tech sector and 21% of US computer science degree earners being women. One study showed that code written by women was approved the first time round more often than men’s, but only if the gender of the coder was hidden. If the gender was revealed, the data showed that women coders received 35% more rejections of their code than men.

Race and ethnicity disparities in tech are also concerning. Looking at the US and a report from the McKinsey Institute of Black Economic Mobility, Black people make up 12% of the US workforce but only 8% of employees in tech jobs. That percentage is even smaller further up the corporate ladder, with just 3% of tech executives in the C-suite being Black. It’s believed that the gap will likely widen over the next decade.

Nurturing AI as responsible guides

During our ‘Navigating AI together’ roundtable, an analogy was shared: AI is like a toddler trying to cross a busy road. Like how we wouldn’t allow a toddler to wander into traffic alone, we must hold the hand of AI and safely guide it.

We need to understand the EDI landscape thoroughly first, becoming adept guides before we can expect AI to generate outputs that are genuinely inclusive and authentically representative. As humans, we need to be responsible AI users, always giving a guiding hand. The first step to making AI an ally to inclusive communications is self-reflection.

Navigating our human bias

We’re human, and we’re fallible, and it is important to remember that in the context of EDI.

In one study, researchers observed 9-month-old babies, evenly divided between Black and white infants. They were all equally exposed to both Black and white adults, all unknown to them. The white babies consistently gravitated toward the white adults, while the Black infants showed a preference for the Black adults. This inclination toward familiarity emerged as early as nine months, suggesting an inherent comfort with those we perceive as similar.

As humans, we tend to categorise. We employ schemas and, yes, stereotypes as well. It’s a coping mechanism and our brain’s attempt to simplify the barrage of information we encounter daily. Yet, this simplification comes with a call for heightened awareness. We need to consciously slow down, be vigilant and actively recognize these tendencies within ourselves.

Increasing awareness of our unconscious biases

Unconscious bias refers to the automatic attitudes and stereotypes that influence our judgments and actions without our conscious awareness. Shaped by our experiences and societal influences, these biases impact how we view others.

If you’re considering using AI within your communications, then you must understand what your own unconscious biases are. The Harvard IATs – Implicit Association Tests – are a useful tool to help you begin to do this.  Set up by a collaboration of US researchers in 1998 Project Implicit aims to collect data on our biases as we learn about ourselves.  We’d recommended picking one identity characteristic you think you don’t carry bias on and one you think you do – and see how it plays out.

Exploring bias in generative AI

Moving on from understanding why generative AI contains bias and recognising how our biases influence our perceptions, let’s shift our focus to examining the actual AI outputs. You likely have already encountered biased outputs from AI, but in our session, we made several comparisons between the results of Google’s image search results algorithm and the outputs from generative AI tools ChatGPT and Midjourney.

Let’s start with a familiar scenario: the image of a courier. When you think of a courier – the person who delivers your Amazon packages – what’s the immediate mental picture that springs to mind?

A quick Google image search result shows a courier as a man carrying a box, often with a van. This representation is the outcome of the content humans have uploaded – it’s not a product of machine learning.

Now, let’s compare it to what AI, drawing from its training data, perceives as a courier’s life.

When we prompted ChatGPT to describe a day in the life of a courier, it conjured a narrative around a character named Jake.

Similarly, looking at Midjourney’s output, we have images suggesting men with boxes and motorbikes as representations of couriers.

Over the course of the roundtable, we shared and discussed many examples showing the bias of AI. To get a better understanding of this, we recommended watching Amy Web’s presentation at the Nordic Business Forum. Amy revealed how AI mirrors human biases. From CEOs to tampons, AI struggled.

It’s safe to say that AI does not challenge the perception of who a person could be. It often reflects society’s most ingrained stereotypes at us and fails to accurately reflect a range of EDI characteristics that humans have.

AI and authentic representation

There are only four EDI identity characteristics that we see or perceive easily – tone of voice, mannerisms, attire, and skin colour. Everything else requires more information from the individual. We can’t accurately assume someone’s age, gender, sexual orientation, race or ethnicity.  We can’t assume whether someone has a disability or not.

So how does AI fare when it comes to navigating these visible and invisible EDI characteristics?

If you ask Midjourney to show you construction workers, you’ll likely get something like this, with a clear lack of visible diversity among the four images.

We then asked Midjourney to depict construction workers with a disability. The generated images were all very similar, with three of the four depicting the construction worker as a wheelchair user.

We then asked Midjourney to depict LGBTQIA+ construction workers. This output really shows the propensity of AI to stereotype.

When it comes to minority groups, AI seems to at best lean on lazy stereotypes, and at worst create an offensive parody of reality. These results show how important it is for us to be hyper-aware of EDI within our communications when using AI, and to hold the hand of that toddler crossing the road tightly!

How to make AI an ally to inclusive communications

As the human communicators guiding the hand of AI, reducing our personal bias has to be the first step:

• Engage in the Harvard IATs to heighten awareness of your unconscious biases
• Be prepared to get it wrong and learn from your mistakes
• Evaluate the diversity in your social and professional circle
• Challenge yourself to culture-add, not culture-fit
• Practice active listening, valuing others’ perspectives over your own voice

With that foundation in place, our top tips for reducing AI bias are:

• Craft prompts carefully to guide unbiased outcomes
• Offer contextual details for to help AI better understand your expectations and requirements
• Fact check for genuine and authentic representation in all AI-generated content
• Offer corrective feedback to steer AI responses towards inclusivity
• Develop ethical guidelines for all AI users and undertake through training

Reach out to us or Ali for a deeper conversation on how you can cultivate a culture that embraces and understands the value of DEIB within your organisation.

To join our upcoming ‘Navigating AI Together’ session in 2024, please send an email over to hello@somethingbig.co.uk to stay in the loop.

AI can be a scary topic. For many the opportunity for a big productivity boost is sitting alongside fears around role replacement and the devaluing of skills. When we heard these concerns from fellow communicators, we knew we needed to help. Our ‘Navigating AI Together’ forum is supporting communicators to manage the transition to AI together, safely, ethically, and with positive and open mindsets. 

In our most recent session of Navigating AI Together, we delved into the current state of AI, strategies for enhancing communication accessibility and inclusivity, the importance of AI transparency, and even took a deep dive into the fascinating realm of AI voice cloning. 

In previous sessions we have: 

• Explored the role AI in communications, including the challenges and opportunities. 
• Shared a guide to prompting, tailored to communication professionals. 
• Discussed the creation of policies for responsible AI usage and user accountability. 
• Provided a review of Midjourney. 
• Examined AI-assisted video creation. 

The current state of AI

In the latest ‘Navigating AI together’ session we reflected on the rapid growth of AI, especially with the recent emergence of generative AI, symbolised by ChatGPT’s meteoric rise. With the genie now out of the bottle, the AI landscape is evolving exponentially, leading to an influx of uses, applications, and platforms. However, experts are suggesting that we may not experience another technological leap of this magnitude anytime soon. Our collective responsibility is now to maximize AI’s potential while adhering to clear usage guidelines and responsible practices. 

Notably, a concerning statistic has emerged, revealing that 73% of users trust content generated by generative AI. This really shows the importance of close supervision in AI-generated content, especially in the communication field, where reliability and truthfulness are paramount. 

As for legislation and regulation, while it may be in development, progress will be slow and may not fully address the intricacies of AI usage. We believe that it’s time for the communications industry to take the lead in setting its own guidelines for AI usage. 

However, despite all the disruption, there is a positive note. AI is already making a substantial positive impact in various domains, from improving cancer screening to addressing climate change, conserving wildlife, and fighting world hunger. The potential for AI to do good is vast and exciting. 

How AI can enhance communication accessibility

Our role as communication professionals includes making our communication as effective as possible and ensuring it is accessible to everyone. Currently, fewer than 4% of the world’s top million websites are accessible to people with disabilities. AI can help accelerate progress in this regard by simplifying and enhancing communication: 

• Copy simplification with AI editors – Tools like Hemmingway can simplify and improve readability, making communication more accessible.
• AI prompts for readability – Using AI prompts to tailor text for different reading levels, cultures, and languages.
• Digital signing – New platforms in development, like Signapse, will be able to create sign language from text or audio, making communication accessible to people who use sign language.
• Translation – AI can help level up and speed up translation, providing accurate and natural translation, learning from feedback over time.
• Image descriptors – Tools like Verbit can create audio descriptions of images in real-time.
• Text to Speech / Speech to Text – Enhances accessibility for various communication modes.
• Multi-Lingual Chatbots – Assist in multilingual communication.

The importance of AI transparency

During the forum we addressed the significant issue of transparency in AI. We posed thought-provoking questions to the group about transparency and shared considerations for when, how, and whether to be transparent in our AI usage.  Our conversations showed that transparency in AI isn’t a straightforward, black-and-white matter; rather, it exists on a spectrum with shades of grey. Determining when to be transparent about our use of AI can pose significant challenges. 

Regulation has already driven the need for transparency in various digital domains, such as cookies on websites and advertisements in social media. Just as privacy regulations have mandated the disclosure of cookie usage, AI may could follow a similar path. Users may come to expect clear information about when AI is involved in content generation, and it may be time for communicators to rise to this challenge without the need for legislation. 

AI voice cloning 

Voice cloning tools use AI and deep learning algorithms to replicate and mimic human voices. These tools analyse the vocal characteristics, pitch, tone, and nuances of a person’s voice from a sample of audio recordings. Once trained, they can generate speech that closely resembles the original speaker’s voice, allowing for the creation of natural-sounding, synthetic voices. 

AI voice cloning has numerous applications, from creating realistic voice assistants to generating voiceovers for content. However, it also raises ethical concerns about potential misuse and impersonation, highlighting the need for responsible use and regulation in this rapidly advancing field. 

We investigated several voice cloning tools and shared our findings with the group’s attendees. If you’d like to find out more then please reach out. 

Navigating AI together: overcoming bias and achieving inclusion 

In our next session we will examine the issue of the biases embedded in AI and explore how we can mitigate this bias and harness AI tools to foster greater inclusion and authentic representation.

Book your place here.

Let’s continue Navigating AI Together, ensuring responsible, ethical, and inclusive AI usage in our communication practices.

Some view AI as a tool for enhancing productivity, while others are understandably expressing concerns about its impact on jobs and the value of creative and communication skills. Recognising these concerns among our network of communication professionals, we’ve established a safe space for collaborative learning about AI and its ethical, responsible usage. Our commitment is to empower our community to embrace AI positively and with an open mind as we collectively explore its potential.

In our second ‘Navigating AI Together’ roundtable held in September, we delved into AI policies and governance, AI-assisted video creation, and shared our review of the generative AI tool Midjourney. One significant takeaway from the discussion was that while AI may boost productivity, it isn’t necessarily reducing workloads; it simply reshapes it.

For insights from our first roundtable, check out the write-up here, where we explored how communications influences workplace culture, employee experience, productivity, sales, customer service, and innovation.

AI insights: policies and governance

We were pleased to be joined by marketing expert, Danny Philamond, from fellow B Corp business, Magnus Consulting. Danny has been advising clients on AI usage, and during our discussion, he shed light on the importance of creating AI policies and governance.

Potential risks of AI:

When considering risks, we focused on marketing and communications:

• Sharing confidential data with third parties poses a significant risk. For example, OpenAI (the creators of ChatGPT) say within their terms of service that they may share data with their vendors (which is potentially up to 80 plugins as of writing). Anything you share with an AI tool has a potentially massive reach. However, within ChatGPT for example you can look to limit this extension by deselecting chat history and training, reducing your data transfer.
• When using an AI tool, think about whether you would want the information to be made public.
• Even if information isn’t strictly confidential, it might still be privileged. Consider whether you’d want AI to learn your product strategies, and potentially share that insight with competitors.
• If you’re using your knowledge and experience to refine AI outputs, and then feeding those back into the model, you’re enabling your unique insights to train the AI. Is that something you want to freely share?

Guidance for advising teams and suppliers:

Emphasise responsible usage:

• Individual accountability is crucial, as policies can’t cover every AI use, given the rapid evolution of the field.
• Maintain transparency, indicating when content is AI-generated.
• Integrate AI usage, accountability, and transparency into your due diligence processes.

Brands and transparency:

• Nearly three-quarters of consumers believe that brands should disclose the use of AI-generated content, according to a recent IPA study. Currently, it’s up to brands to decide on transparency.
• Some AI companies, including OpenAI, Alphabet, and Meta, have made voluntary commitments to watermark AI-generated content, which could become enforced regulation.
• Consider the impact of transparency: imagine if Photoshop or Instagram filters were required to disclose image alterations when they first became popular. Such transparency could have positively affected the growing challenges we’re seeing around self-esteem and mental health. We have the opportunity, and perhaps the moral responsibility, to be transparent about AI-generated content.

Break down company-wide AI policies:

• Build flexibility into policies, as the AI landscape evolves rapidly. Plan regular policy reviews.
• Provide training on the guidelines, ensuring everyone understands AI terminology and limitations.
• Support teams in utilising AI tools for efficiency while managing associated risks.

Recommendations for AI policies and guidelines:

As a starting point, all policies should consider:

• User accountability and responsible usage.
• Best practices for effective AI usage.
• Safe AI usage.
• Activity to avoid and risk factors.
• Data handling and protection.
• Compliance and governance.
• Training and feedback loops.

AI use case: Exploring AI-assisted video creation ​

During the previous session, we found that the vast number of AI tools and opportunities was overwhelming to many communicators, and so during this session, we turned our focus to just one potential use case: AI-assisted video creation. We shared an example of an AI-assisted video that we would be able to produce for clients, using the example of translating an employee policy handbook into a digestible animation (please get in touch if you’d be interested in watching this video and finding out more about the process involved). These videos can be quick to create, have the potential to be considerably more affordable than traditional video, be translated into multiple languages and can bring inaccessible documents to life.

After viewing the video, our group identified that AI-assisted video creation can be a solution for communication projects that often receive limited attention and budget, such as:

External communications:

• Product descriptions
• Platform demos
• Customs advice
• Product or service specifications
• Regulatory advice

Internal communications:

• Health and safety materials
• Employee handbooks
• Systems training
• Onboarding documents
• Policy materials

AI platform review: Midjourney

Midjourney is a generative AI program and service that produces images from natural language descriptions (called prompts). After submitting a prompt, Midjourney generates four different images, which you can then edit, or tailor your prompt to refine the concepts. Midjourney can create any style of image you can think of. Within our Midjourney platform review, we cover how to use it, subscriptions and licensing, prompt writing, and the pros and cons of using the platform from a communications perspective. You can download the full platform review here.

AI can be an emotional topic, and for many, the opportunity for a big productivity boost sits alongside fears around role replacement and the devaluing of skills. Hearing concerns from fellow communicators, we have created a forum ‘Navigating AI together’ to enable us to manage the transition to AI together, safely, ethically, and with positive and open mindsets.

In our first roundtable, we discussed how communications is a driving force that shapes workplace culture, employee experience, productivity, sales, customer service, and innovation. We know it’s not time to hand over communications to robots, but rather to put our focus on leveraging the potential of AI, alongside human expertise. Here is a summary of some of the key conversations that were had during the first ‘Navigating AI together’ roundtable.

AI and communications: setting the scene

At the recent Simply IC conference, established internal communicators explored the impact of AI in their field. During the discussions, they found that ‘AI is generally welcomed by the communications community although still quite scary’.

In a reassuring address at the Simply IC conference, generative AI expert and author Nina Schick emphasised that AI makes communication more important than ever. Instead of replacing the role of communicators, it is likely to highlight the need for real human communication.

Additionally in the roundtable, we discussed how uptake of AI might be slower than the media would suggest. Insights from a survey of 2,000 people in the US shed light on the current state of mainstream AI usage. The results indicated that AI adoption remains relatively limited, with only one in three individuals having tried AI-powered tools. Moreover, most people are not familiar with the companies responsible for these innovations. Notably, younger generations, particularly millennials, lead in embracing AI, while boomers appear to lag in its adoption.

Opportunities and challenges in AI for communicators

Communicators are often juggling large workloads, always trying to do more with tighter budgets and tighter deadlines. If your CEO came to you today and said I’m giving you a budget for an extra head in your team, their role is just to support you, you probably wouldn’t say no. AI has the potential to be a very useful tool in the box.

During our first ‘Navigating AI together’ roundtable, communicators identified several opportunities surrounding AI in communications:

• Simplifying contracts and legal language, making complex concepts understandable.
• Distilling white papers and reports for easier comprehension with tools like ChatPDF.
• Supporting pre-meeting research, providing insights for better preparation.
• Quickly generating thought-starters and creative prompts with tools like AI.
• AI-powered voice narration making video content a more accessible and affordable channel (while considering concerns around cloning voices and deep fakes).
• Ensuring content from multiple sources has a consistent tone of voice.
• Boosting the accuracy, speed, and accessibility of data analytics.
• Accelerating the content creation processes, acting like an intern while prioritising accuracy.
• Supporting annual and quarterly reporting, especially in understanding legislation, regulations, and sustainability challenges.

However, with great power comes great responsibility. The communicators attending the roundtable were cautious of the risks around AI, including:

• The potential for content plagiarism.
• Voice and video cloning leading to the threat of deep fakes.
• Rapid advancements impacting job roles.
• The need to double-check all AI-generated content for consistency and accuracy.
• Over-reliance on AI, leading to dependence issues and deskilling.
• The limitations AI has in intelligence, only being able to use borrowed information.
• Ambiguities in policies, guidelines, and law.
• The ethical considerations surrounding original IP, ideas and, creative.

Navigating AI together: overcoming bias and achieving inclusion

In our next session we will examine the issue of the biases embedded in AI and explore how we can mitigate this bias and harness AI tools to foster greater inclusion and authentic representation.