Artificial Intelligence is here, and Signal is already looking for first-of-its-kind ways to test its capabilities. Manager Alexa Velickovich breaks down how Signal worked closely with the Environmental Defense Fund (EDF) to conduct a comprehensive survey of the media landscape surrounding: 1) climate change, 2) the agriculture sector, and 3) financial solutions, carbon markets, and financial risks – all by harnessing the power of AI. Learn more below and read her full article on the project here.
AI Case Study One Pager
Signal + Environmental Defense Fund
The Power of AI in Media Analysis: A Case Study in Collaborative Innovation
One of the world’s leading international nonprofit organizations, Environmental Defense Fund (EDF) creates transformational solutions to the most serious environmental problems. To do so, EDF links science, economics, law, and innovative private-sector partnerships. Through its Climate-Smart Agriculture workstream, EDF works closely with farmers, policymakers, food companies, and more to develop solutions to expand the use of climate-smart practices to increase food production for a growing population, rapidly reduce powerful pollutants like methane and nitrous oxide, and make rural communities more resilient.
Challenge
Seeking to amplify coverage of its farm finance and agricultural carbon markets work in mainstream media outlets and influential financial sector trade publications, EDF worked with Signal Group to conduct a comprehensive survey of the media landscape surrounding the intersection of: 1) climate change, 2) the agriculture sector, and 3) financial solutions, carbon markets, and financial risks.
Data Deluge to Strategic Insights
Traditional media analysis and monitoring approaches lacked the capability to survey such a large scope and analyze trends to increase EDF’s share of news coverage on its climate-smart agriculture work. To tackle this challenge, Signal employed a groundbreaking approach – harnessing the capabilities of the OpenAI[i] API[ii] to analyze a significantly larger sample of media articles than traditional methods allow.
In collaboration with Conlan Scientific, a financial data science consultancy firm, Signal extracted the necessary data via custom web-scraping[iii] tools. Finding topic-specific articles from myriad publications required investigation into how each website functioned and trust that the news organizations had properly defined how coverage was categorized.
With the data extracted, Signal began processing the articles through GPT.[iv] By utilizing GPT, Signal was able to efficiently clean and organize the resulting dataset and create a comprehensive media resource of high-profile, English-language media explicitly related to climate, finance, or agriculture published within the last two years. The dataset was then analyzed by human experts, including an experienced team of media relations experts, to identify valuable trends and key insights that could be translated into actionable recommendations that would assist in EDF’s goal.
Armed with the combined insights from GPT and expert analysts, Signal provided EDF with a clear roadmap for navigating the media landscape. The thorough media strategy encompassed not only current needs but also offered valuable insights for shaping future media relations initiatives, highlighting the necessity of combining AI analysis with human expertise.
Employing both machine-driven and manual experience-driven analysis to understand and vet the dataset was critical in providing a usable product that successfully met the client’s needs, especially given the novelty of using AI to conduct a large-scale media analysis. While AI is powerful, human oversight remains crucial for guiding AI-powered tools, interpreting data, and translating insights into actionable recommendations.
Human-AI Partnership
The key to success lies in balancing the innovative potential of AI with the nuanced understanding and strategic insight that only human expertise can provide.
During a panel at the 2023 World Economic Forum’s Growth Summit, Richard Baldwin, an economist and professor at the Geneva Graduate Institute in Switzerland, assured the audience there was nothing to worry about. “AI won’t take your job,” he said. “It’s somebody using AI that will take your job.”
GPT’s ability to process large datasets efficiently and at a lower cost than traditional methods mark a significant advantage in handling big data for media analysis, but it cannot be stressed enough – the tool is only as capable as the person who wields it. AI, while able to add great value to work, is not infallible. No matter how much information it has access to, as long as humans remain fallible, so will AI.
Beyond the Algorithm
The future of media analysis lies in AI-powered solutions, requiring public affairs and strategic communications teams to broaden their skills to include data analysis and technical fluency. AI is not a substitute for humans, but those who don’t learn to adapt will be left behind.
Investment is necessary to build expertise. The real power of AI centers around knowing the right tool to work with, learning how to harness its capabilities, and understanding its basic operational guidelines to produce effective results. Without that foundational knowledge, lack of experience will lead to suboptimal results and wasted potential.
However, let me be clear: the answer is not to abandon employees without this foundational knowledge in favor of new AI talent. Instead, the focus should be on upskilling existing talent, leading to a ‘best of both worlds’ solution. In addition to closing the knowledge gap, future AI-powered media analyses would benefit from a well-defined workflow to enhance efficiency and effectiveness, as well as refined methodologies to help translate data insights into strategic media recommendations.
Ever-evolving AI technology requires users to grow alongside it, continually adjusting and adapting to benefit from its potential. This constant transformation means all stakeholders – data scientists, analysts, communications experts, and clients – are essential to include in every aspect of the project lifecycle. Involving key stakeholders throughout the process leverages their knowledge and contextualizes findings, leading to deeper insights, quicker turnaround, and valuable strategic media recommendations.
The Path Forward
After successfully achieving EDF’s goals using AI, it is clear there is a definite market need for AI-powered media analysis services, and the process is only going to get better, faster, and ultimately, smarter, allowing for more time to be spent on strategy and growth. With some improvements and overall refinement, there is an enormous opportunity ahead for public affairs and strategic communications professionals to offer additional AI-powered services layered with indispensable human expertise. The future of media analysis lies in effective communication, responsible integration, and human-machine collaboration.
[i] OpenAI is an artificial intelligence research organization dedicated to advancing the field of artificial intelligence (AI) and making AI technologies more accessible. OpenAI has developed and released several products aimed at this mission, including, GPT, OpenAI DALL-E, and more.
[ii] API (Application Programming Interface) is a set of rules, protocols, and tools that allows different software applications to communicate with each other. The OpenAI API is a platform that allows developers to access and leverage artificial intelligence models developed by OpenAI.
[iii] Web scraping, or web data extraction is data scraping used for extracting data from websites.
[iv] GPT (Generative Pre-trained Transformer) models are trained on vast amounts of text data and can generate human-like text, translate languages, answer questions, summarize text, and perform various other natural language processing tasks.