-          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

• 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.

• 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 

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.

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.