David Clinch, VP of Partnership at Mather Economics and MD at Media Growth Partners, discusses the trade-offs between building and buying AI tools in newsrooms. He emphasizes the importance of focusing on specific needs and workflow alignment when evaluating AI tools. The role of human involvement in AI decision-making and the evolving nature of jobs in newsrooms are also explored. The podcast concludes with a discussion on collaboration with tech companies and the impact of AI on journalism.
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Quick takeaways
Building bespoke tools for specific needs can be more effective than buying generic tools, optimizing workflow efficiency and decision-making in newsrooms.
When considering AI tools, it is crucial to prioritize tools that support journalism, evaluate vendors with a journalism background, and focus on streamlining newsroom workflows with tools that aid in creating newsletters, videos, or article summaries efficiently and accurately.
Deep dives
The Dilemma of Building vs Buying AI Tools for Newsrooms
One of the key questions newsrooms currently face is whether to build or buy AI tools. While building AI tools allows for greater control, it comes with substantial development and cost. On the other hand, buying AI tools can accelerate deployment but may result in less control. According to David Klinch, a blended approach is advisable. Publishers should avoid building what they don't need and instead invest in building bespoke tools for specific needs. However, for generic or existing tools that meet requirements, it is more cost-effective to buy. By blending build and buy strategies, newsrooms can optimize workflow efficiency and make informed decisions.
Evaluating AI Tools for Newsrooms: Qualifications and Thresholds
When considering AI tools, three qualifications are crucial. Firstly, AI tools should support journalism rather than replace it. Tools that can write entire articles without human involvement pose reputational risks. Secondly, it is essential to evaluate vendors that have a background in journalism or journalism-focused tools. Their understanding and ethical approach ensure high-quality outcomes. Thirdly, the effectiveness of the tools in streamlining newsroom workflows is crucial. Tools that aid in creating newsletters, videos, or article summaries efficiently and accurately are highly valuable for newsrooms.
The Distinction between Machine Learning and Generative AI
Machine learning and generative AI are not synonymous. Machine learning tools operate by using controlled data sets and established rules, while generative AI involves more extensive language models. Machine learning in journalism has been useful in accelerating processes with controlled data, but generative AI raises concerns due to its black box nature and the potential risks associated with accessing unreliable sources. The best approach is to ensure that generative AI only works with trustworthy, controlled data sets and adheres to ethical guidelines to avoid potential pitfalls.
The Role of AI in Facilitating Subscription and Revenue Strategies
AI can assist newsrooms in developing subscription and revenue strategies. By leveraging AI tools, publishers can optimize content pricing, create newsletters, and recommend suitable articles for readers. However, careful consideration should be given to ensuring that AI remains human-guided and works exclusively with authorized data sets. Publishers should prioritize delivering value through original journalism and collaborate with AI companies that are willing to pay for access to high-quality journalism. Collaborative approaches between newsrooms and AI companies offer potential opportunities to enhance journalism's reach and impact in the digital era.
David Clinch, the Vice President of Partnership at Mather Economics and Managing Director at Media Growth Partners, joins Nikita Roy to discuss the critical choice between building or buying AI tools in newsrooms. With his extensive experience advising major publishers, David sheds light on how AI is reshaping newsroom strategies and the critical trade-offs news organizations face in the era of AI adoption.
David has worked as an international journalist at ITN and CNN, and then as a media executive at both Storyful and Mather Economics.Throughout his three decade career at the intersection of the news and technology industries David has created an unrivaled network and a skill set built on direct experience of innovative journalism and successful business strategies in the digital age. From his time as an early evangelist for the adoption of digital technology and social media at CNN, David has become an expert in both the opportunities and risks involved in connecting journalism to technology.
Helping to build a successful digital news organization at Storyful also helped him understand what is involved in developing a business strategy that can build sustainable growth and diversified revenue streams. This passion for journalism and the appropriate application of digital technology and resources is at the core of David's current work at MGP, helping news organizations not only survive, but thrive, in a way that has a real impact in society.
🎧 Tune in for valuable insights into the decision-making processes for publishers grappling with the "build vs. buy" dilemma for AI tools.
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