Medium: Funnel AI | Machine Learning for Investigative Journalism and Business
FunnelAI uses natural language processing, a branch of machine learning, in order to connect businesses to their customers. Our advanced algorithms help companies and teams to maximize their uniquely human skills by providing them with the customers who have the intent to purchase their product.
However, technology companies are not the only organizations using machine learning to help people reach their full potential. News organizations are increasingly using machine learning techniques to identify trends, process data, and aid investigative reporting. As Wired reported last year, Reuters is implementing a tool called Lynx Insight, which will help reporters analyze data and brainstorm story ideas.
Reg Chua, an executive at Reuters focusing on data and innovation, noted that Lynx insight is intended to augment human capabilities. “The goal is it adds value to what they would done, and frees them up to pursue angles that would have taken them longer to get to,” he told Wired.
FunnelAI has a similar approach to using machine learning. Like Reuters, we leverage technology to allow companies to focus on their uniquely human capabilities. We empower our users to creatively use their marketing and sales resources to reach out to their customers in real time.
While papers such as The Washington Post are using AI to write entire stories about local sports and other formulaic subjects, the trend of machine learning in journalism primarily involves human and machine collaborations. For example, The Atlanta Journal-Constitution used machine learning in an investigation into sexual misconduct and abuse by doctors.
In 2016, the paper collected 10,000 disciplinary documents and used machine learning to identify whether the records were related to sexual misconduct. “We then created a computer program based on machine learning to read each case and, based on key words and their relationship to each other as well as other factors, give each a probability rating that it was related to a case of physician sexual misconduct,” The Atlanta Journal-Constitution said.
The Atlanta Journal-Constitution story became nationally recognized as a powerful example of how machine learning can help journalists expose abuses of power. Other examples of the technique used in journalism are BuzzFeed News’ investigation into hidden spy planes, ProPublica’s identification of congressional policy priorities and political messaging, and the New York Times’s tagging/annotation prototype.
Although innovations in journalism were not the focus of Human + Machine: Reimagining Work in the Age of AI, a book published earlier this year by Accenture executives Paul R. Daugherty and H. James Wilson, it is clear that these innovations are an example of smart organizations filling the “missing middle.”
As Human + Machine explains, machines in the “missing middle” will help augment human capabilities by completing tasks and collecting data that improves productivity. News organizations and businesses alike are taking advantage of these new collaborations to, as the authors say, give humans superpowers. The “missing middle” is exactly where FunnelAI operates. Learn more about how we are using machine learning to help you maximize your organization’s potential.