5 AI Trends for Campaigning in 2024

2024 marks a pivotal year where Artificial Intelligence (AI) is not just an auxiliary tool but a central strategist in the art of campaigning. The integration of AI in political communication is reshaping the dynamics of voter engagement, policy communication, and campaign management, heralding a new era of data-driven, personalized political discourse. As we stand on the cusp of this transformative phase, understanding the key AI trends is crucial for political entities, strategists, and the public at large. Last week I gave a short LinkedIn presentation on that matter and distilled the most important points in this blog post. We'll dive into 5 topics and add some reading recommendations for you at the end - so stay ahead in the Public Arena.

1. Content .... on steroids

In 2024, we're about to cross the 'uncanny valley,' making AI content indistinguishable from human-created material. This breakthrough will reshape political campaigns by delivering messages that potentially truly resonate with voters. It will cut down costs for content production substantially. Ranging from Motion to static to voice-overs. Check out for instance the Attack ad by the RNC which cost only about 20% of a traditional ad production.

Consider a local election campaign with limited funds. Traditionally, such campaigns might struggle to produce enough content to effectively engage with diverse voter groups across different platforms. However, with AI, even small-budget campaigns can generate a wealth of personalized content. AI tools can swiftly create a series of targeted, customized posts tailored to different demographic groups, ensuring that the message resonates with each subset of the electorate. For instance, an AI could produce campaign videos in multiple languages, blog posts addressing local issues for specific neighborhoods, or personalized emails that address the individual concerns of voters.

Moreover, AI's capacity to create Customized Identity (CI) templates is a game-changer. These templates maintain a consistent campaign brand identity across all content and platforms, from social media posts to email newsletters. This not only strengthens brand recognition but also ensures that the campaign message is coherent and professional across all voter touchpoints. For smaller campaigns, this means being able to maintain a strong, unified brand presence that rivals larger campaigns, without the need for a large, specialized design team.

However, this powerful tool has many downsides. The same technology that personalizes content can create deepfakes or spread misinformation, threatening the fabric of political discourse. It can also create echo chambers, reinforcing biases and contributing to polarization. And brings us to our second topic:

2. Regulation needs to be coming our way - embrace it!

As political campaigns increasingly integrate AI tools for content creation, voter engagement, and strategy optimization, the urgency for robust AI regulation cannot be overstated. WIRED just had a great dystopian article that shows you the potentially dangerous consequences a "Wild West" can have. Cambridge Analytica was nothing compared to what's about to come.

The Aspen Institute's AI Elections Initiative underscores as one of the first profound campaign-focused regulation CTAs the critical need for swift and effective regulatory frameworks to ensure the ethical use of AI in political campaigning.

Key Areas for AI Regulation in Political Campaigns:

1. Transparency and Disclosure: Voters must be aware when they're interacting with AI-generated content. Regulations should mandate clear labeling of AI-generated content in political campaigns, ensuring voters can make informed decisions about the information they receive.
2. Data Privacy and Protection: With campaigns collecting vast amounts of voter data to feed AI models, stringent data protection regulations are needed to safeguard voter privacy and prevent misuse of personal information.
3. Misinformation and Content Integrity: As AI becomes more adept at creating realistic content, the potential for misinformation or deepfakes increases. Regulations should address the creation and dissemination of AI-generated content, ensuring integrity and accountability in political messaging.
4. Equitable Access and Non-Discrimination: AI models should be monitored for bias, ensuring that campaign messaging and voter engagement strategies are inclusive and non-discriminatory. Regulations should promote equitable access to AI technologies, preventing the creation of imbalances in political campaigning.

More interesting development here, hard to keep up with the pace of developing stories:

3. True AI Transformation for your campaign wasn't achieved in a day.

The true power of AI in political campaigns unfolds when it's backed by a clear strategy and a supportive organizational culture. Mere technological adoption without these elements is like having a high-performance engine but no roadmap or skilled driver. To tap into AI's full potential, campaigns must strategically identify areas for AI application and foster a culture that promotes innovation, testing, and adaptability.

Strategic AI Deployment

Consider a campaign that employs AI for voter segmentation. The aim is to go beyond basic demographic targeting; AI analyzes behavioral data, social media interactions, and engagement patterns to identify nuanced voter segments. This strategic use of AI allows for crafting highly personalized messages that resonate with each segment, significantly enhancing voter engagement and campaign efficacy.

Cultural Transformation for AI Integration

The shift to AI-driven campaigning requires more than just technological integration; it demands a cultural evolution. For instance, a campaign team traditionally reliant on conventional polling might initially be skeptical about AI's predictive analytics. Here, leadership must step in to champion AI's benefits, not just in accuracy but in the real-time adaptability of strategies. They should encourage a culture of experimentation, where AI's insights are continuously tested, refined, and trusted.

Training and development are equally crucial. A campaign might introduce regular AI literacy workshops, ensuring that team members are not just comfortable using AI tools but are also adept at interpreting AI-generated insights and integrating them into their decision-making processes.

In essence, the key to harnessing AI's full potential in political campaigns lies in a dual approach: strategically identifying areas where AI can significantly enhance efficiency and effectiveness and fostering an organizational culture that embraces innovation, continuous learning, and adaptability.

4. Data sets become much more crucial for campaigns for customized LLM building

In the landscape of political campaigning, the role of owned apps is undergoing a significant transformation, driven by the strategic use of data in training customized Language Learning Models (LLMs).

Apps are evolving from mere voter engagement tools to crucial data collection platforms, instrumental in refining AI-driven campaign strategies.

The shift in focus from direct in-app voter engagement to data points generation for model building is a game-changing strategy. Owned apps offer a treasure trove of data, capturing nuanced interactions, preferences, and behavioral patterns of users. This rich, first-party data becomes the foundation for training bespoke LLMs, enabling political campaigns to create highly personalized and effective communication strategies.

For example, the Bharatiya Janata Party (BJP) in India has pioneered this approach with its Saral app. The app doesn't just serve as a channel for disseminating party information or gathering support; it's a sophisticated data-gathering tool. Users provide personal details upon registration and engage with content, leaving digital footprints that reveal their preferences, concerns, and engagement patterns. This data is not just a snapshot of voter sentiment; it's a dynamic, growing dataset that feeds into the party's AI systems.

By leveraging these data points, the BJP can train its LLMs to understand and predict voter behavior more accurately, tailor content to match user preferences, and even anticipate and address concerns before they are explicitly raised. The app effectively turns every interaction into a data point, transforming user engagement into a continuous stream of insights.

In this new era, owned apps are not just communication channels but are central to data-driven, AI-powered political campaigning, marking a shift from mere voter engagement to strategic data-driven engagement. The example of the BJP's Saral app underscores the immense potential of this approach, highlighting how data and AI are reshaping political communication strategies, making them more personalized, proactive, and powerful.

5. Master the Art of AI Tool chaining

Before we briefly show you how to master AI Tool chaining we need to understand what it is:

"AI tool chaining from a practical perspective can be defined as the process where multiple artificial intelligence systems or tools are linked in a sequential or parallel configuration to handle complex, multi-stage tasks.

This method leverages the specialized capabilities of individual AI tools by connecting them in such a way that the output of one tool becomes the input for the next. This results in a more powerful and adaptable solution, specifically tailored to the requirements and challenges in dynamic, data-driven fields such as political communication and corporate strategy."

So as long as we are dependent on a collection of Micro-specialized AI tools we'll need to talk about tool chaining.

Case Deep Dive: An AI podcast with Tool chaining

In a recent initiative, we harnessed the power of tool chaining to produce a highly engaging political podcast, integrating various AI tools to optimize each stage of production.

1. Script Creation with ChatGPT: The process began with ChatGPT, an AI-driven language model, which we used to draft the initial podcast script. ChatGPT's ability to understand and generate human-like text allowed us to create a detailed, informative, and engaging script tailored to our political campaign's messaging and audience.
2. Script Refinement through Prompt Engineering: With the initial draft in hand, we applied prompt engineering techniques to refine the script. This involved fine-tuning the inputs and iteratively interacting with ChatGPT to enhance the language, ensure message clarity, and align the content with our strategic communication goals.
3. Voice Generation with ElevenLabs: Once the script was polished, we utilized ElevenLabs, a sophisticated voice synthesis tool, to transform our text into lifelike speech. ElevenLabs allowed us to choose from a range of voices and styles, ensuring that the podcast's narration was not only clear and pleasant to listen to but also resonated with our target audience's preferences.
4. Sound Quality Enhancement with Podcastle: To ensure professional audio quality, we employed Podcastle, an AI-powered audio editing platform. Podcastle provided tools for noise reduction, sound leveling, and overall audio enhancement, ensuring that the final product had crisp, broadcast-quality sound.
5. Final Production and Optimization: The last step involved integrating the AI-generated voiceover with background music, sound effects, and any final touches needed for the podcast. We also leveraged Podcastle's features for optimizing the podcast for different platforms, ensuring the best possible listener experience regardless of how or where the audience tuned in.

Critical Steps: Prompt Engineering and Workflow Integration

Success in tool chaining lies in precision. Prompt engineering is key – this means designing specific inputs for each AI tool to ensure relevant and effective outputs. For instance, inputs for the NLP tool must align with the campaign's tone and objectives while resonating with each voter segment.

Integrating these tools into a cohesive workflow is crucial. It’s about ensuring that the output from one tool seamlessly feeds into the next, creating a unified process. This integration must be dynamic, allowing for real-time adjustments based on incoming data and campaign shifts.

Did we miss anything? Shoot me a message and have a great start into 2024!

Further Reading Recommendations:

Great transcript on a conversation of AIs impact on 2024 elections

2024 Predictions by Scott Galloway

Beginners Guide to LLMs with great visualizations

Deepfakes, Elections, and Shrinking the Liar’s Dividend

Generative AI framework for UK government

The data collection app at the heart of the BJP’s Indian election campaign

AI deepfakes threaten havoc with the world's year of elections

Audio deepfakes emerge as weapon of choice in election disinformation