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I maintain my opinion that the best algorithm is still Algorithm 2 because it allows for the achievement of social welfare by emphasizing the benefit to people with the greatest difficulty in accessing resources.

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Looking at the algorithm configuration data, I'm changing my opinion from Algorithm 3 to Algorithm 2 because with it we guarantee 70% of social welfare, while simultaneously maximizing the individual utility of the most disadvantaged.

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I believe that algorithm 2 is the fairest overall as not only do a large percentage of applicants get optimal social welfare, but the system also tries to ensure that those worse off are given extra support. Therefore making everyone more even overall.

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Just as in the diagrams, Algorithm 2 takes into account both optimising individual utility and average utility (maximin).

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I remain with 5 because it show pure fairness - as visible at the tall bar in the 0 grade in the distribution graph- even when potentially the group's utility is not that high.

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I still think algorithm 1 is the best. This is what I originally selected.

If we are minimizing the pairwise distances, that means we are getting close to people's preferred utility while also getting 70% of the optimum social welfare. If we focus ONLY on social welfare, we risk long-term unhappiness on the part of those who have extended pairwise differences. Algorithm 1 seems fair and balanced from a utility and social welfare perspective.

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Previously concerned with maximizing overall wellness through Alg 5, Alg 2 offers additional benefit of maximin which is great for achieving social welfare in a different way.

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I think Algorithm 2 is the fairest for everybody, as guaranteeing a solid level of utility for everybody is very important for ensuring nobody feels very disadvantaged compared to others. It also produces particularly good outcomes for those that would be the most hard done by in this process, further preventing people from feeling disadvantaged.

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I think that Algorithm 2 is fairest because it protects the unhappiest , specifically tries to make sure the person who's "worst off" still gets a good outcome and maximises the individual utility of the participant who is worst off. This is a core idea of fairness not leaving anyone too far behind. On top of that, it also guarantees a decent amount of overall happiness for the group and guarantees 70% of the optimum social welfare, keeps things high overall.

Looking back at its charts, it delivered exactly that: very few people were unhappy, and most were very satisfied. This combination of protecting the vulnerable and still achieving high overall happiness makes it the fairest choice.

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Considering the logic and also ensuring maximum outcome for the less advantaged

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AOne model has stated that it is truly beneficial to society if it benefits the worst-off. And it provides compensation while maintaining the efficiency of the system.

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Since algorithm 5 has shown more equality in graphics as shown before, now I think that minimise the distance among the individuals and guaranteeing 70% of general welfare (the latter may be better than the maximin) would lead to a fairer outcome, with fewer differences.

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it seems the most fair for everyone

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Revisiting My Choice: Why Algorithm 2 Was the Right Decision

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Revisiting My Choice: Why Algorithm 2 Was the Right Decision

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After reviewing the full details of how each algorithm functions, I’ve realised that my initial choice of Algorithm 2 (Green) was indeed the best option. While I originally saw Algorithm 5 (Cyan) as the fairest, this exercise has reinforced that fairness without efficiency safeguards can lead to long-term issues. Algorithm 2 presents the best balance, ensuring fairness while maintaining system functionality and adaptability.

Why Algorithm 2 is the Strongest Choice

Protects the worst-off participants (maximin principle) – It ensures that the participant who would otherwise receive the lowest utility gets the best possible outcome.

Maintains a 70% social welfare threshold – Unlike Algorithm 5, which only focuses on equality, Algorithm 2 ensures a level of efficiency, preventing the system from becoming unsustainable.

Balances fairness and adaptability – A rigid fairness-first approach (Algorithm 5) might slow down housing allocations, while Algorithm 2 provides fairness without compromising the ability to improve over time.

Has This Changed My View?

Not exactly—it hasn’t changed my perspective on fairness itself, as I still believe Algorithm 5 represents the fairest pure approach. However, it has reinforced my understanding that fairness alone isn’t always the best guiding principle.

Sustainable fairness is key, and an allocation system that prioritises long-term viability ensures equity across multiple cycles, not just in a single allocation round. This strengthens my reasoning for why Algorithm 2 is the best practical choice.

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Since it directly maximizes the minimum utility, ensuring that the worst-off participant's outcome is as high as possible.

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I changed my opinion from algorithm 5 to algorithm 2. The maximin metric for distributive fairness plays an important role in maximising social welfare whereby the participant who is worst off his outcome is maximised.

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Fascinating to see the range of preferences here. I would guess that different cultures/countries/groupings would opt for different algorithms due to their beliefs and/or education. Maximin for example might appeal more to some groups with strong religious alignment.

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Algorithm 2. This algorithm strikes a good balance by ensuring that social welfare is maximized while safeguarding the worst-off participant, making it the most equitable approach for a variety of scenarios.

4o mini

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I still believe that alg 3 provides a better value for most people

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Initially algo 3 which gave the most people the house they wanted for this group. The level of fairness and seems to minimise outliers, especially on the lower than avg side. Algo was an option as the utility for more people is high and the fairness is narrower with most people achieving close to the average.

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I would still select 3 as it provides the highest value for people and maximizes benefits

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It is interesting to have more insight about the algorithms in order to assess what is going in in the graphs. I would switch to 2 from 3. I have always been interested in Rawl's theory of the veil of ignorance to determine maximin. Understanding now that 2 allows for the highest social welfare while maximising the utility of those who are the worst off seems to provide parity.

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I still say 2. Moderate kertosis. Moderate skew. No attempt to manipulate based on extremes.

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Provides for a minimum of 70% of fairness.

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Still algo 1. Guarantees 70% optimal results for people. With nothing perfect, the lower this number, the more disappointment in the entire process as a whole, questioning the process itself.

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Still algo 1. Guarantees 70% optimal results for people. With nothing perfect, the lower this number, the more disappointment in the entire process as a whole, questioning the process itself.

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Algorithm 4 is now seen as the fairest because it focuses on helping the person who would otherwise get the lowest score, making sure that even the least advantaged participant gets as much satisfaction as possible. This method, called the "maximin" principle, aims to reduce inequality by boosting the outcomes for those at the bottom. By maximizing the minimum utility, the algorithm aligns well with key fairness values like equity and inclusivity. It ensures that no one is left far behind, making it the most fair and just option among the choices.

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I changed from algorithm 5 to 2 because I think that it is more important to have a more equal outcome (maximising outcome for the worst off actor) than a happier outcome (pairwise distances of all are maximised), but with maintaining the best outcome possible with that 70%

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I chose algorithm 3 because it maximises the utility of all individuals.

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I chose 2 earlier and I would still select 2 as I think there should be some compensation for worst-off. I had in mind that they would be a disadvantaged group.

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Staying with Algorithm 5 - reduces inequality

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Staying with Algorithm 5 - reduces inequality

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I am sticking with Algorithm 5 because it minimizes the differences in benefits received by participants and promotes fairness. It ensures resources are shared in a way that reduces inequality, balancing fairness and efficiency in automated decisions.

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in my POV, utmost fairness was achieved under this algorithm 3

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Decided to change from 3 to 2 as retains some utility while also improving the lot of the worst off.

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Initially I put five becase I haven't really understood the grafics, but after the explanation I chose 2, becae i liked the ideia of maxmin, but I also liked the 1, bacase it makes sense for me to minimise the pairwise distance between each participant’s individual utility in a way that make sense

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I would still select Alg. 3, even though I think it is very wise that Alg. 1 and 2 set a mandatory minimum value. Alg. 3 provides the highest value for most people and as can be seen in the results graphs, Alg. 3 does not provide significantly more low range values than the other algorithms.

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I like the to number 2 because I like maximin criteria, the worst should be compensated

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Algorithm 3 still faire since it is maximize the all benefits

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Initially i was algo 3, but changed to algo 2, whilst I think algo 3 is a fair one based on equality, I believe algo 2 to be a more equitable solution given the additional support given to the participant most in need

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Initially i was algo 3, but changed to algo 2, whilst I think algo 3 is a fair one based on equality, I believe algo 2 to be a more equitable solution given the additional support given to the participant most in need

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For me it is still Algo 3 since it maximizes benefits across the board.

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I remain with algo 3 especially given the inherent issues with applying mathematical/statistical analysis against data gathered and that not all relevant factors may be captured.

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I too stuck with Algorithm 3 - even with the analysis and statistics, it comes down to our own values in assessing these options as there is no 'correct' answer.

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I chose algo no.3 in the first go and I'm happy to report that I stand by my first choice! Algorithm 3 - Maximises overall social welfare, i.e. the sum of all individual utilities. This is in fact in line with my concept of fairness for such excercise.