01/29/20 – Rohit Kumar Chandaluri – An Affordance-Based Framework for Human Computation andHuman-Computer Collaboration

January 30, 2020January 30, 2020 Rohit Kumar Leave a comment

Summary:

The author explains the research going on in the visual analytics area to collaborate the work between humans and computers. While there have been multiple promising examples between human-computer collaboration but there are no proper solutions to the following questions

How can we tell if a problem will benefit from collaboration?
How do we decide which tasks to delegate to which party and when?
How can one system compare to others trying to solve the same problem?

The author tries to answer to the above questions in the paper. While the author explains the uses of visual analytics that exist in the present world and their usages. The author then explains the different kinds of affordances that exist in the visual analytical human computer collaboration and explains each affordance in detail further.

Reflections:

It was interesting to learn that visual analytics can be seen as a human computer collaboration. For analytics on large data we need larger computation power to visualize the analytical data. It was interesting to learn about the white box human computer collaboration and black box human computer collaboration. The visual analytics help people with no expertise in the are to provide inputs to the problem.

Questions:

How can we be sure that one visualization is the correct solution for a particular problem?
The people who are developing the visualization tools are the humans, will the area of expertise of the people developing the tool affect the results?
Is visual analytics solution is better than normal machine learning solution to solve the problem?

01/29/20 – Rohit Kumar Chandaluri – Human Computation: A Survey and Taxonomy of a Growing Field

January 29, 2020January 30, 2020 Rohit Kumar Leave a comment

Summary

The author of the paper started explaining about human computation, crowd sourcing, social computing, data mining, and collective intelligence and the differences between these terminologies. The author also explained the intersection of these areas and the areas where they are disjoint. After that the author explained about different dimensions of human computation work to control the work quality, in which each dimension has many values. And the author explained each value and its contribution to the system. And in the final area the author proposed possible future research areas that can be researched for new topics in this area.

Reflections

It was interesting to know how quality control is handled in human computations given money is involved people try to exploit the system.
Money is not the only factor that motivates people to work in this area there are many incentives that motivate people to complete this task.
There are different methods that exist to control the quality of work like review, voting, economic modeling, input-output agreement and automatic check etc.
The process order of the task also has a significant meaning for each task.

Questions

Is the present system for quality check enough to ensure quality? There might be tasks which might need expertise in which none of the workers exist to complete tasks.
Can collection of data can be considered as crowdsourcing, where we need images of different people for image recognition model?
Do you think 90% jobs that provide pay of less than 0.1$ die after some time due to the need for expertise?

01/22/20 – Rohit Kumar Chandaluri – Ghost Work

January 28, 2020January 28, 2020 Rohit Kumar Leave a comment

There is a lot of work going on in the present technologies with out us knowing about them like identifying hate speech or abusive speech etc. All this work is done by a computer software which we call it as Artificial Intelligence. It is hard for a software alone to classify all the possible scenarios in the world to hate speech or not. So, we train the software by providing it with some sample data and labels telling this sentence is hate speech and this is not. This data that is required by the software is provided by humans, so for a software to evolve like a human robot it requires the intervention of humans for it to develop. The chapters provided explain how these data labelling is achieved and how did jobs like crowdsourcing and Mtruck developed in the course of 10 years. It also explains how these jobs help software systems to evolve, and how these jobs are paid on contract basis. There are no legal laws that bind these jobs to provide basic necessities like health insurance, food etc., the pay for the job is decided by supply of labor for that job and in some cases the pay will be less than the minimum pay required. The chapters also explain how macro and micro jobs get crowdsources for very low payments making the jobs expand to any kind of area.

The chapters brought about interesting topic on how crowd source can be used for very low prices. And it is also interesting to see people making living out of these kinds of jobs. It was true that the jobs are interesting and not mundane as you change your job for each different task which makes your like non mundane. The chapters didn’t explain how the crowd source work is validated, which I am interested to learn about. It is interesting to learn that we can break a big task into small micro or macro tasks and get them done at a very cheaper price using crowdsourcing. It was interesting to learn that there are internal crowd source jobs that exist in companies like Microsoft, Google etc.

Will the jobs like these develop more and cause full time jobs at stake as these kinds of jobs can be used for any areas like education (projects, assignments) and even macro tasks in the big projects?
How are people making a living out of these jobs by getting paid less than minimum wage, there are people who just do these jobs?
How is validation of these jobs getting done, how can you make sure that the task completed by the crowd source worker was good?
As the crowd source jobs are helping create automated software’s which will remove jobs of the people who are doing it as of now, it will also remove the jobs of simple tasks in crowd sources too as once the software is developed to uncover corner scenarios we need experts which only few people will be eligible. Is crowd source creating jobs or removing them?