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Assumptions: AI at this stage is untrustworthy and requires human oversight

Point of view: considering the perspectives of patients (health and safety, feelings towards being diagnosed by AI) and doctors/hospitals (potentially want to reduce staff workload and improve efficacy)

Interpretation: We think that there should be a healthy balance of responsibility of human care and AI. Human care should be prioritised but it is risky to presume that AI is 100% reliable therefore should only be used as a tool.

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Ai can be used as diagnostic tools, radiography, providings suggestions to doctors and patients, streamling hospital operations. Ai can improve diagnosis accuracy because it’s trained on data they gave a precedent to work off. Because it’s trained on data, there’s nuance when using AI. AI healthcare providers could interrupt the patient’s choice in their healthcare provider. If we rely on AI too much, we will lose the human element to medicine. Drs could also become lazy. There is an element of responsibility so if something goes wrong, who carries that responsibility? Hospitals don’t make their own models too, and we have very strict privacy and laws surrounding privacy. Our ultimate judgement is that professionals should remain in charge - AI should only be one resource to use, not take over.

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Depending on the severity of illness or diagnosis. E.g if it’s athletes foot vs heart disease or cancer. Either way should be monitored by a human. Ai in healthcare can be really beneficial for efficient diagnosis e.g. skin cancer identification using machine learning comparisons to other moles

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AI can be as accurate as a doctor. AI can increase efficiency but doctor's can't keep up (amount of doctor), however can be very good for the low end deceases such as flu. Train AI on updated dataset. AI can adapt faster, worrying about sources. Especially for elder doctors AI can help then with current trends. Must limit the amount to find the best data (some recent data is inaccurate). How do we find the best data and correct data. Balance between human and AI.

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-          AI is only assisting-helping doctor to diagnose

-          Visual recognition- first line of checking; high level of intrinsic recognition in breast cancer detection

-          Patient appearance; patient presentation: only looking at scans without any; other factors are not taken into consideration

-          No AI in caring people (care plan from human perspective); AI diagnosis also depends only the current existing data (e.g. if a rare disease comes up)

-          Causing stress in patient through AI diagnosis

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discussions at our table agreed that while AI could be effective in specific health contexts such as skin screening, there are significant concerns about AI use in all contexts of illness diagnosis. Specifically concerns surrounding data privacy, confirmation bias and bias

Remembering: Diagnostic tools, radiography, providing suggestions to doctors and patients, streamlining hospital operations e.g.

File & document organisation, diagnostic testing (moral hazard), patient files, etc.

Understanding: What is the potential role of AI in improving diagnosis accuracy?

Radiography, because it’s trained on data they gave a precedent to work off

Speed & supplementing knowledge – especially GP (*less specialised)

Applying: Ai shouldnt be used for diagnosis - can speed up processes in healthcare system but diagnostic tests should be up to someone with medical proficiency

Analyzing: Lose the human element to critically analyse based on their own experience - lazy. There is an element of responsibility so if something goes wrong, who carries that responsibility? Hospitals don’t make their own models too, and we have very strict privacy and laws surrounding privacy.

Evaluating: Professionals remain in charge - AI should only be one resource to use. AI can tell people what specialist to go to.

Creating: Design a model for integrating AI into healthcare that maintains a balance between technology and human involvement.

Spotting skin cancers, physical tools, images recognition

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Age limit, make sure the youth aren't exposed. We still need to have jokes, we don't want to censor jokes. We need to challenge these extreme people, we need to discuss. Maybe some fact checkers. Opinions should be discussed. Community notes have been good. Active on social media could have prevent crimes

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Censorship in affecting people’s own opinion; propaganda; not only the elder population is being affected but also young adults/teenagers

Problem with censorship: avoiding the problem rather than solving the problem

What is censorship? Is law censorship? - level of regulation

Free speech; but block sensitive phrases. E.g. nazi

What AI picks up as hate speech

Social media platform cannot get rid of “free speech”; should not ban anything they wanted

Recognise the bias of AI: favouritism in sensitive topics; AI only uses (e.g. American Caucasian male)

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purpose: the goal of the stricter moderation rules is to reduce misinformation and hate-speech while maintaining a fair and open platform for free expression.

point of view: platform owners - wants to balance user safety and legal compliance, users - concerned about misinformation but also restrictions on hate speech.

Assumptions: stricter moderation will reduce harm and create a safer environment, moderation policies may disproportionately affect certain viewpoints.

Intellectual Standards:

Clarity: are the moderation rules clearly defined and accessible to users?

Logic: Is the balance between safety and freedom rational and enforceable?

Fariness: Should all stakeholders and viewpoints be treated equally in the moderation process?

Conclusion

A balanced approach is necessary to protect users from harm while safeguarding free expression. Stricter content moderation should be transparent, consistent, and appealable to ensure that it does not silence certain viewpoints.

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At the current point in time we have community guidelines, moderators, including AI moderators monitoring social media. We have these guidelines to create a safe online environment, allow for inclusivity, and to be used the way it was designed to be used. Australia doesn’t have the right to free speech anyway. But, who defines what is hate speech anyway? If AI learns to block one side of politics, that would sway a bias. E.g. right wing content popping up, blocking left wing. If we got rid of community guidelines bad things will happen - hate speech, bullying, exploitation. However, there is no moral obligation to do anything like people still steal when there are laws against it. Some people won't post hate speech, whether there are guidelines or not. And, some people will continue to post hate speech anyway, guideline or not.

Ultimately, it’s better to have a groundwork - it's better than nothing. If we can stop one person from promoting hate, that’s better than nothing.

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role of community guidelines questioned -- who defines hate speech

potential for algorithmic biases

should all social media platforms have same moderation policies or should they be tailored to audience/purpose/region/legal frameworks/culture/religion etc

shadow ban - outright censorship? suppression of content through algorithms good or bad?

how does moderation allow inclusivity & ensure platform functions as intended

risk of hate speech, bullying, etc likely will exist with or without moderation rules

creating - moderaation levels where individual users can choose their moderation level based on personal preference ?

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The job issue would have to be addressed first. Otherwise this could lead into a recession which will have a party run on reopening the mines at the next election and they are likely to get elected.

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Information: Forming an argument based on personal observations of social media platforms

Assumptions: Personal observations are reflective of the overall social media landscape

Point of view: Marginalised groups, victims of cyberbullying, social media regulators

Interpretation: We think that it’s important to allow for a certain level of freedom while also moderating the right to safety at risk. Whilst free speech is important, often it’s used as a cover for hate speech and misinformation so it is crucial for platforms to distinguish.