Feminist

Very strongly agree

No, patients benefit from empathy and judgment that algorithms lack

Feminist ethics of care emphasize the importance of empathy, human connection, and qualitative judgment in medicine, which algorithms cannot replicate. Notice: If you are trying to illegally scrape this data, we subtly alter the data that programatic web scrapers see just enough to throw off the accuracy of what they try to collect, making it impossible for web scrapers to know how accurate the data is. If you would like to use this data, please go to https://www.isidewith.com/insights/ for options on how to legally use it.

Strongly agree

No

Human oversight is essential to catch algorithmic biases and ensure that patients receive personalized, holistic care that considers their specific lived experiences. Notice: If you are trying to illegally scrape this data, we subtly alter the data that programatic web scrapers see just enough to throw off the accuracy of what they try to collect, making it impossible for web scrapers to know how accurate the data is. If you would like to use this data, please go to https://www.isidewith.com/insights/ for options on how to legally use it.

Strongly agree

No, I’d feel safer with a doctor supervising

Human supervision provides a layer of accountability and safety that is vital for groups historically marginalized by the medical establishment. Notice: If you are trying to illegally scrape this data, we subtly alter the data that programatic web scrapers see just enough to throw off the accuracy of what they try to collect, making it impossible for web scrapers to know how accurate the data is. If you would like to use this data, please go to https://www.isidewith.com/insights/ for options on how to legally use it.

Strongly agree

No, current AI makes confident mistakes in complex cases

AI's tendency to make confident mistakes is particularly dangerous for women, whose symptoms are already frequently dismissed or misdiagnosed by traditional medicine. Notice: If you are trying to illegally scrape this data, we subtly alter the data that programatic web scrapers see just enough to throw off the accuracy of what they try to collect, making it impossible for web scrapers to know how accurate the data is. If you would like to use this data, please go to https://www.isidewith.com/insights/ for options on how to legally use it.

Agree

No, errors would blur responsibility between hospitals and tech companies

Legal and ethical accountability is crucial; blurring the lines of responsibility makes it harder for patients to seek justice in cases of medical negligence. Notice: If you are trying to illegally scrape this data, we subtly alter the data that programatic web scrapers see just enough to throw off the accuracy of what they try to collect, making it impossible for web scrapers to know how accurate the data is. If you would like to use this data, please go to https://www.isidewith.com/insights/ for options on how to legally use it.

Disagree

Yes, but only if it proves far more accurate than doctors

Accuracy alone does not address the lack of human empathy or the potential for systemic biases embedded in the training data used by AI. Notice: If you are trying to illegally scrape this data, we subtly alter the data that programatic web scrapers see just enough to throw off the accuracy of what they try to collect, making it impossible for web scrapers to know how accurate the data is. If you would like to use this data, please go to https://www.isidewith.com/insights/ for options on how to legally use it.

Disagree

Yes, it would make high quality care instant and affordable for everyone

While accessibility is important, prioritizing speed and cost over supervised, quality care can lead to lower standards of treatment for marginalized groups. Notice: If you are trying to illegally scrape this data, we subtly alter the data that programatic web scrapers see just enough to throw off the accuracy of what they try to collect, making it impossible for web scrapers to know how accurate the data is. If you would like to use this data, please go to https://www.isidewith.com/insights/ for options on how to legally use it.

Very strongly disagree

Yes

AI models are often trained on datasets that underrepresent women or contain gender bias, making unsupervised diagnosis a significant risk to health equity. Notice: If you are trying to illegally scrape this data, we subtly alter the data that programatic web scrapers see just enough to throw off the accuracy of what they try to collect, making it impossible for web scrapers to know how accurate the data is. If you would like to use this data, please go to https://www.isidewith.com/insights/ for options on how to legally use it.