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Home Trends

How Health Journalists See AI

Freelancing watchdogs

Jay K Joshi by Jay K Joshi
June 13, 2024
in Trends
0
How Health Journalists See AI

Mike Hindle

Health journalists perceive artificial intelligence (AI) as a valuable instrument to augment their journalistic endeavors and capacity to deliver news. This technology empowers journalists to explore subjects with greater depth, although it may introduce unexpected sources of bias.

Journalists are increasingly open to utilizing artificial intelligence in their work, recognizing its potential to streamline processes and improve efficiency. However, many still hold reservations about AI taking over the creative aspect of writing. They prefer to use AI as a tool for research and fact-checking, rather than as a means to author articles.

Despite this reluctance, journalists are excited about the possibilities AI offers in terms of connecting with audiences in new and innovative ways. The use of AI in journalism allows for personalized content recommendations and targeted messaging, enhancing the reader experience. In this way, AI can help journalists reach a wider audience and engage with them on a more meaningful level. While there may be concerns about AI replacing human journalists, it is clear that its integration into the field can lead to significant advancements and opportunities for growth.

The increasing reliance on the internet for healthcare information has opened up new avenues for journalists to amplify the narrative surrounding important health issues and counter the spread of misinformation. The current industry trend leans toward freelance work, which makes it crucial for journalists to be able to contribute more to a story than before when many had the support of an entire newsroom. Harnessing artificial intelligence will become essential for journalists to streamline their work without sacrificing their unique voice and journalistic perspective.

Yet, finding the right balance in utilizing this technology remains a challenge, as many journalists are still navigating its capabilities and limitations. Moving forward, the most successful journalists will be those who can effectively integrate AI into their reporting while maintaining their integrity as storytellers. Yet many do not realize that AI has evolved to where journalists can leverage specific digital tools to enhance specific aspects of their work.

Transcribing interviews:

With the introduction of AI-powered tools, the landscape of journalism documentation is experiencing a significant shift towards efficiency and accuracy. This technological advancement is revolutionizing the way journalists conduct interviews and manage source materials, making the process more streamlined and reliable. Gone are the days of manually transcribing interviews, as AI tools can now provide fast and accurate transcriptions within a matter of minutes. This not only saves journalists valuable time but also ensures that the information captured is more precise and comprehensive.

Automating repetitive tasks:

Rather than spending hours transcribing interviews or sorting through countless emails, AI technology can efficiently handle these tasks, saving journalists valuable time and energy. This means that journalists can now dedicate their efforts to conducting in-depth research, interviewing sources, and crafting compelling stories. By streamlining these mundane tasks, AI enables journalists to produce higher quality content and deliver more insightful reporting to their audiences.

Analyzing large data sets:

Through the processing of vast amounts of data from public records and social media, AI has the ability to uncover hidden stories and trends that traditional investigative journalism may have overlooked. This powerful tool has significantly increased the efficiency and speed of conducting thorough investigations, allowing journalists to delve deeper into complex issues and uncovering insights that were previously hidden. The combination of AI technology and journalism has opened up a new frontier in reporting, enabling journalists to produce more in-depth, data-driven stories that provide a deeper understanding of the world around us.

Fact-checking articles:

AI tools play a crucial role in enhancing ethical journalism by reviewing articles for bias and fact-checking claims. By utilizing artificial intelligence, news organizations can promote balanced reporting and combat misinformation. These tools are able to analyze large amounts of data quickly and efficiently, helping to ensure that journalists are presenting accurate information to their audience.

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Jay K Joshi

Dr. Joshi is the founding editor of Daily Remedy.

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Videos

In this episode, the host discusses the significance of large language models (LLMs) in healthcare, their applications, and the challenges they face. The conversation highlights the importance of simplicity in model design and the necessity of integrating patient feedback to enhance the effectiveness of LLMs in clinical settings.

Takeaways
LLMs are becoming integral in healthcare.
They can help determine costs and service options.
Hallucination in LLMs can lead to misinformation.
LLMs can produce inconsistent answers based on input.
Simplicity in LLMs is often more effective than complexity.
Patient behavior should guide LLM development.
Integrating patient feedback is crucial for accuracy.
Pre-training models with patient input enhances relevance.
Healthcare providers must understand LLM limitations.
The best LLMs will focus on patient-centered care.

Chapters

00:00 Introduction to LLMs in Healthcare
05:16 The Importance of Simplicity in LLMs
The Future of LLMs in HealthcareDaily Remedy
YouTube Video U1u-IYdpeEk
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AI Regulation and Deployment Is Now a Core Healthcare Issue

Clinical Reads

Ambient Artificial Intelligence Clinical Documentation: Workflow Support with Emerging Governance Risk

Ambient Artificial Intelligence Clinical Documentation: Workflow Support with Emerging Governance Risk

by Daily Remedy
February 1, 2026
0

Health systems are increasingly deploying ambient artificial intelligence tools that listen to clinical encounters and automatically generate draft visit notes. These systems are intended to reduce documentation burden and allow clinicians to focus more directly on patient interaction. At the same time, they raise unresolved questions about patient consent, data handling, factual accuracy, and legal responsibility for machine‑generated records. Recent policy discussions and legal actions suggest that adoption is moving faster than formal oversight frameworks. The practical clinical question is...

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