None of (a) to (c) are correct

The whole article was retracted

All of (a) to (c) are correct

The inaccurate citation of Charles Mills was corrected

The deadnaming of the trans woman was removed

It is wrong to subscribe to a belief without evidence

We should practice tolerance to create a better society

Faith is justified when adequately supported by evidence

Everyone has a right to freedom of religion

it offered insufficient money to attract good candidates

Apple immediately brought out something better

it recommended overpaying applicants

it systematically preferred male to female candidates

Establishing ethics boards and committees to oversee the use of AI.

Oversight by human beings for important decisions.

Adding noise to data sets to obscure individual data points, and so protect the privacy of individuals.

Placing emphasis on the enforcement of existing laws and regulations.

Interfering with the data set to ensure certain errors don't occur.

They could teach users so many social skills that they become too cool for their human friends.

They could become artificial general intelligences and break out of their guardrails.

They can encourage risky behaviour such as self-harm.

Most experts agree that all of the above are likely risks of AI companions.

Both of the above are examples of feedback loops.

While looking at clips on men's mental health issues, Jim clicks on an Andrew Tate video. His TikTok feed then makes further suggestions of Andrew Tate videos, even though he doesn't like any of them on the platform. His feed soon becomes populated with Andrew Tate and Jordan Peterson.

Neither of these are feedback loops

Stephanie watches Seven Samurai on Netflix. This results in Netflix recommending further samurai movies. Stephanie tries a couple, but only watches a few minutes of them. She nevertheless gets more foreign language martial arts movies recommended, and watches some of these. After a while, much of the Netflix feed is made up of foreign language films.

ensuring dissenting opinions are present in the data set so that there is a proper diversity of opinions 

a method that adds noise to training data to obscure individual data points, thus protecting the privacy of individuals in the data set

teaching the AI to be polite and non-combative in its interactions with people, no matter the provocation

creating adversarial robustness

introducing made up examples into AI training sets in order to identify likely mistakes