How to Take Notes with Gemini on Google Meet

Controversy Around Google Meet

With the introduction of Gemini and similar AI-driven tools, Google Meet has sparked both excitement and significant debate, particularly around privacy and data security. While Gemini’s AI-powered note-taking and transcription features promise improved productivity, they also introduce complex issues around data handling, user consent, and corporate influence.

Privacy Concerns with AI-Powered Transcription and Note-Taking

Gemini’s AI note-taking and transcription functionalities involve recording, transcribing, and summarizing conversations in real-time. This capability raises critical questions about the privacy of sensitive discussions—especially in sectors like healthcare, finance, and law, where confidentiality is paramount. Participants in these meetings may worry that their conversations are stored, analyzed, or even accessed by Google for improvement of the AI, sparking debates around user control over their own data.

Google’s Data Storage and Handling Practices

Google, as one of the world’s largest tech companies, has a history of accumulating vast amounts of data on its users. While Google claims that user data is stored securely and with a focus on privacy, the sheer scale of Google’s reach means that even seemingly benign data, like meeting transcriptions or AI-generated summaries, could contribute to a larger data pool that fuels Google’s AI training and development. For many, this raises concerns about where their data goes, how long it is retained, and whether Google uses it beyond what’s strictly necessary for Google Meet functionality.

Compliance with Organizational and Regional Regulations

As companies across various regions use Google Meet, Google faces the challenge of complying with privacy regulations such as the GDPR in Europe or CCPA in California. These regulations require stringent data protection and privacy measures, but it remains unclear how Google ensures compliance across all regions where Gemini is available. Organizations need to be aware of these regulatory requirements and consider whether the data collection practices align with their own compliance standards. This can place additional administrative burdens on businesses, especially those handling sensitive information.

Corporate Influence and Monopoly Concerns

Google’s substantial influence in the tech industry has led to ongoing conversations around corporate dominance and market monopolization. With tools like Gemini, Google is solidifying its position not only as a search engine or cloud service provider but also as an AI-driven workspace ecosystem. For businesses and consumers, this can create a dependency on Google’s products, potentially limiting access to diverse alternatives. Google’s power to shape how millions conduct virtual meetings—and the data that results from them—raises questions about fair competition and whether smaller companies can realistically compete with Google’s integrated and increasingly AI-driven environment.

Transparency and User Consent

One of the biggest concerns around AI tools like Gemini is transparency. Although Google has made strides to improve its privacy policies, there remains a need for clearer, more accessible information on how Gemini’s AI interacts with user data. For instance:

• How is consent managed for all meeting participants, especially in cross-organizational meetings?
• Are users fully informed about how their conversations might be used for machine learning or AI development?

These questions underline the need for clear opt-in processes and explicit user agreements for Gemini’s AI tools, especially in settings where participants may not be familiar with Google Meet’s privacy protocols. Additionally, even with security measures in place, some users remain wary of Google’s ultimate intentions with this data, especially given Google’s financial interest in developing AI products.

User Control Over Data

Many users and organizations are calling for more robust control over their data, such as the ability to easily delete transcriptions or recordings after a meeting. Google Meet currently allows hosts to delete meeting recordings from their Drive, but users have limited options for managing or removing AI-generated notes and transcriptions. Increased user control over Gemini’s data handling could mitigate some privacy concerns, allowing individuals to decide how long their data is retained or whether it’s used to improve Google’s AI models.

Public Controversy: Image Generation and Ethical Concerns

One of Gemini’s earliest and most high-profile controversies involved its image generation capabilities. In an attempt to reflect the diversity, the AI produced historically inaccurate and, at times, offensive visual depictions, such as Black Vikings, Asian women in World War II-era German military uniforms, and even a female Pope. These images sparked widespread criticism and raised questions about how the model had been trained to interpret historical and cultural context.

Public figures including Nate Silver and Elon Musk added their voices to the backlash. Silver questioned how the AI handles ethically complex topics, while Musk—who has his own AI company and a well-documented history of inflammatory public commentary—accused Gemini of ideological bias. Many saw Musk’s comments as more performative than constructive, but the combined pressure led Google to temporarily suspend image generation for people and issue a formal apology.

The incident became a flashpoint in broader debates around AI responsibility, bias, and training data. Like many large-scale AI rollouts, Gemini’s reception highlights the growing need to balance innovation with cultural sensitivity and user trust.

Balancing Convenience with Privacy

While Gemini brings undeniable convenience, it prompts users to balance these benefits against potential privacy risks. For many organizations, Gemini’s capabilities will offer time-saving and productivity-enhancing features. However, the trade-off is entrusting a significant amount of data to a company already criticized for data collection practices. Users and organizations may need to carefully weigh the value of AI-driven insights against the importance of data autonomy and privacy.