Table 12.
Assignments of the Found Statements About Artificial Intelligence
| Source | Statement | AI Function |
Facilitation Activity |
|---|---|---|---|
| Abhinav et al. (2018) | Acts as a virtual buddy for the worker and helps them throughout their career journey | Acting | Worker Motivation |
| Abhinav et al. (2018) | Pro-actively supports worker’s needs | Acting |
Contribution Support |
| Abhinav et al. (2018) | Data-driven advice to worker. | Generating |
Contribution Support |
| Abhinav et al. (2018) | Helps the user to navigate crowdsourcing platform | Acting | Crowd Coordination |
| Abhinav et al. (2018) | Guides the user towards the most appropriate tasks | Acting | Goal Orientation |
| Abhinav et al. (2018) | Recommends the best career path progressions and skills to train in | Generating | Worker Motivation |
| Abhinav et al. (2018) | Recommends tasks to workers based on worker’s preference, | Generating |
Task Communication |
| Abhinav et al. (2018) | Predicting fitment of a worker with the selected task, id est., how fit a worker is for the selected task | Predicting | Task Design |
| Abhinav et al. (2018) | Recommends the right marketplace to the crowd workers based on profile information | Generating |
Task Communication |
| Abhinav et al. (2018) | Identify the goal of the worker | Recognizing | Goal Orientation |
| Abhinav et al. (2018) | Presents the response to the worker in a conversational interface. | Generating |
Contribution Support |
| Abhinav et al. (2018) | Keeps track of the worker’s status and activities on the platform | Reasoning |
Performance Monitoring |
| Gimpel et al. (2020) | Facilitator in achieving consensus within crowd discussions efficiently | Acting | Crowd Moderation |
| Gimpel et al. (2020) | Measuring and fostering cross-fertilization | Reasoning |
Performance Monitoring |
| Gimpel et al. (2020) | Lead crowd discussions to better results | Acting | Crowd Moderation |
| Gimpel et al. (2020) | Facilitate online discussions | Reasoning | Crowd Moderation |
| Gimpel et al. (2020) | Decision support in crowdsourcing, yielding more efficient and effective decision-making. | Acting | Decision Making |
| Gimpel et al. (2020) | Track participants’ activity | Reasoning |
Performance Monitoring |
| Gimpel et al. (2020) | Record activity data and calculate statistics by phase and type of activity per participant | Reasoning |
Performance Monitoring |
| Gimpel et al. (2020) | Aggregate activity into relevant KPIs | Reasoning |
Performance Monitoring |
| Gimpel et al. (2020) | Automatically extract activity data | Reasoning |
Performance Monitoring |
| Gimpel et al. (2020) | Enrich activity statistics with background information | Recognizing |
Performance Monitoring |
| Gimpel et al. (2020) | Assess the similarity between contributions | Reasoning | Quality Control |
| Gimpel et al. (2020) | Assess the semantic similarity of pairs or larger sets of contributions | Reasoning | Quality Control |
| Gimpel et al. (2020) | Provide a list of pairs/sets of potentially redundant contributions | Recognizing | Quality Control |
| Gimpel et al. (2020) | Provide a list of similar contributions | Recognizing | Quality Control |
| Gimpel et al. (2020) | Help participants when submitting their contributions to avoid redundancy | Acting |
Contribution Support |
| Gimpel et al. (2020) | Group contributions which are thematically linked and identify the topics of these groups | Reasoning |
Contribution Aggregation |
| Gimpel et al. (2020) | Provide suggestions of clusters, accounting for multiple levels of detail | Reasoning |
Contribution Aggregation |
| Gimpel et al. (2020) | Provide suggestions for groups of contributions, which are easily rearrangeable | Reasoning |
Contribution Aggregation |
| Gimpel et al. (2020) | Identify topic(s) in content groups | Recognizing |
Contribution Aggregation |
| Gimpel et al. (2020) | Assess the knowledge domains captured by contributions | Reasoning |
Contribution Evaluation |
| Gimpel et al. (2020) | Indicate the extent to which knowledge domains are represented per contribution | Reasoning |
Contribution Evaluation |
| Gimpel et al. (2020) | Define a set of knowledge domains relevant to the given task | Predicting | Task Design |
| Gimpel et al. (2020) | Define a set of knowledge domains based on participants’ backgrounds | Predicting | Task Design |
| Gimpel et al. (2020) | Assess knowledge domains covered over time | Reasoning |
Contribution Evaluation |
| Haas et al. (2015) | Predictive model of worker quality to select trusted workers to perform review | Predicting | Crowd Coordination |
| Haas et al. (2015) | A separate predictive model of task quality to decide which tasks to review | Predicting | Quality Control |
| Haas et al. (2015) | Identify the ideal trade-off between a single phase of review and multiple phases of review given a constrained review budget in order to maximize overall output quality | Reasoning | Workflow Design & Selection |
| Haas et al. (2015) | Reduce errors introduced by workers either unintentionally (due to innocent mistakes) or maliciously (due to collusion or spamming) | Recognizing | Quality Control |
| Haas et al. (2015) | Organizes the crowd hierarchically | Acting | Crowd Coordination |
| Haas et al. (2015) | Provides a predictive model of task error | Predicting | Quality Control |
| Haas et al. (2015) | Tracks worker quality over time | Reasoning |
Performance Monitoring |
| Haas et al. (2015) | Promote the most qualified workers to the top of the hierarchy | Decision-making | Worker Motivation |
| Haas et al. (2015) | Selecting tasks to review | Recognizing | Quality Control |
| Haas et al. (2015) | Identify skilled workers | Recognizing |
Participation Encouragement |
| Haas et al. (2015) | Determining the quality of a task | Predicting | Task Design |
| Kittur et al. (2013) | Tasks may be structured through multi-stage workflows in which workers may collaborate either synchronously or asynchronously. As part of this, AI may guide (and be guided by) crowd workers. | Acting | Crowd Coordination |
| Kittur et al. (2013) | Decomposing tasks into subtasks | Acting | Task Design |
| Kittur et al. (2013) | Assignment of tasks in relation to individuals’ abilities | Decision-making | Task Design |
| Kittur et al. (2013) | Guide workers to complete synchronous tasks | Acting |
Contribution Support |
| Kittur et al. (2013) | Automatic assignment of group members to maximize collective intelligence | Decision-making | Task Design |
| Kittur et al. (2013) | Help make the crowd more efficient, skilled, and accurate | Acting | Crowd Coordination |
| Kittur et al. (2013) | Design machine learning algorithms that more deeply understand the human nature of these labels | Reasoning |
Contribution Evaluation |
| Kittur et al. (2013) | Determine which work products may still be improved | Recognizing | Quality Control |
| Kittur et al. (2013) | Assign workers most likely to make such improvements | Decision-making | Task Design |
| Kittur et al. (2013) | Predict their expertise needs in advance, then train and adapt workers in an online fashion via automated tutoring or peer learning | Predicting | Task Design |
| Kittur et al. (2013) | Designing and integrating workflow, incentive, and instruction patterns | Decision-making | Workflow Design & Selection |
| Kittur et al. (2013) | Serve as a reflective aids, encouraging the crowd to learn by pointing out what others have done in similar contexts | Acting | Crowd Moderation |
| Kittur et al. (2013) | Sharing information about workers should be coupled with more robust systems for monitoring and reporting requester abuses | Reasoning |
Performance Monitoring |
| Kittur et al. (2013) | Guiding crowds on which tasks to complete (task assignment) | Decision-making | Crowd Coordination |
| Nagar et al. (2016) | Reduce the cognitive load of expert judges | Acting |
Contribution Evaluation |
| Nagar et al. (2016) | Classify and rate crowd-proposals | Reasoning |
Contribution Evaluation |
| Nagar et al. (2016) | Indicators of the completeness and maturity of the proposal | Reasoning |
Contribution Evaluation |
| Nagar et al. (2016) | Organize the review process somewhat differently, and hopefully, more efficiently | Decision-making | Workflow Design & Selection |
| Nagar et al. (2016) | Prioritize the review sequence | Decision-making |
Contribution Evaluation |
| Nagar et al. (2016) | Automatically scoring these complex intellectual artifacts | Reasoning | Quality Control |
| Nagar et al. (2016) | Aid human experts in the review process | Acting |
Contribution Evaluation |
| Qiao et al. (2018) | Distributes the skillful workers and less-skilled workers | Decision-making | Task Design |
| Qiao et al. (2018) | Determine which worker or group of workers should be assigned tasks | Recognizing | Task Design |
| Qiao et al. (2018) | Records everyone’s work execution time | Reasoning |
Performance Monitoring |
| Qiao et al. (2018) | Maximizes the overall assignment quality | Acting | Task Design |
| Rhyn and Blohm (2017) | Extract useful information from unstructured data | Recognizing |
Contribution Evaluation |
| Rhyn and Blohm (2017) | Cluster ideas | Reasoning |
Contribution Aggregation |
| Rhyn and Blohm (2017) | Selecting novel ideas | Recognizing |
Contribution Evaluation |
| Rhyn and Blohm (2017) | A DSS should identify relevant contributions in the data set. | Recognizing |
Contribution Evaluation |
| Rhyn and Blohm (2017) | A DSS should remove irrelevant contributions from the data set. | Acting |
Contribution Aggregation |
| Rhyn and Blohm (2017) | A DSS should aggregate redundant information for the decision-maker. | Reasoning |
Contribution Aggregation |
| Rhyn and Blohm (2017) | A DSS should prioritize important information for the decision-maker. | Decision-making | Decision Making |
| Rhyn et al. (2017) | Tracking the origin of contributions in crowdsourcing | Reasoning |
Contribution Evaluation |
| Rhyn et al. (2017) | Analyzing their textual characteristics | Reasoning | Quality Control |
| Rhyn et al. (2017) | Identifying the most innovative ones | Recognizing |
Contribution Evaluation |
| Rhyn et al. (2017) | Predictors for innovative contributions | Predicting |
Contribution Evaluation |
| Rhyn et al. (2017) | Evaluation of large amounts of contributions | Reasoning |
Contribution Evaluation |
| Seeber et al. (2016) | Facilitate the development of shared understanding | Acting | Crowd Moderation |
| Seeber et al. (2016) | Improved idea quality | Acting | Quality Control |
| Seeber et al. (2016) | Recommendations could be designed that provide feedforward guidance to extend idea descriptions | Predicting | Crowd Moderation |
| Seeber et al. (2020) | Automatically guide the behavior of humans, such as imposing communication patterns onto the group, asking clarification questions, giving recommendations, or providing feedback | Acting | Crowd Moderation |
| Seeber et al. (2020) | Helps evaluate the consequences of potential solutions | Acting |
Contribution Evaluation |
| Seeber et al. (2020) | Debates the validity of proposed positions offering evidence and arguments | Generating | Decision Making |
| Seeber et al. (2020) | Provides predictions to unstructured problems | Predicting | Task Design |
| Seeber et al. (2020) | Participates in cognitive decision making with human actors | Acting | Decision Making |
| Seeber et al. (2020) | Incorporate and understand emotional signals from humans | Reasoning | Crowd Moderation |
| Seeber et al. (2020) | Support the team in coming up with conclusions | Acting |
Contribution Support |
| Seeber et al. (2020) | Identify certain group dynamics | Recognizing | Crowd Moderation |
| Seeber et al. (2020) | Foster team cohesion | Acting |
Culture Development |
| Seeber et al. (2020) | Mitigating negative cognitive biases | Acting | Risk Management |
| Tavanapour and Bittner (2018) | Facilitation of the idea submission process | Acting |
Contribution Support |
| Tavanapour and Bittner (2018) | Reach each contributor on idea platforms in an initial idea submission process | Acting |
Task Communication |
| Tavanapour and Bittner (2018) | Actively asks questions in one-to-one collaboration and encourages the contributor to think about missing details and add them before the idea is released to the filtering or voting process | Acting | Quality Control |
| Tavanapour and Bittner (2018) | Guide users in such a way that they can more thoroughly elaborate on their ideas | Acting | Crowd Moderation |
| Tavanapour and Bittner (2018) | React correctly to statements | Acting | Crowd Moderation |
| Tavanapour and Bittner (2018) | Actively ask questions | Generating | Crowd Moderation |
| Tavanapour and Bittner (2018) | Lead conversation | Acting | Crowd Moderation |
| Tavanapour and Bittner (2018) | Motivate participants to qualitatively edit initial ideas | Acting |
Participation Encouragement |
| Tavanapour and Bittner (2018) | Display productivity oriented behavior | Reasoning |
Performance Monitoring |
| Tavanapour and Bittner (2018) | Prevent deviation to other topics & guide conversation back to idea | Acting | Goal Orientation |
| Tavanapour and Bittner (2018) | Construct interesting & pleasant conversation | Generating | Crowd Moderation |
| Tavanapour and Bittner (2018) | Provide correct reactions to statements | Generating | Crowd Moderation |
| Tazzini et al. (2013) | Favoring motivation and creative participation among users | Acting |
Participation Encouragement |
| Tazzini et al. (2013) | Track and quantify the contribution of each solver to the final solution | Reasoning |
Performance Monitoring |
| Tazzini et al. (2013) | Boosting motivation | Acting | Worker Motivation |
| Tazzini et al. (2013) | Supporting and driving users creativity | Acting |
Contribution Support |
| Tazzini et al. (2013) | Ensures fairness and objectivity in measuring the contribution of each individual | Acting |
Performance Monitoring |
| Tazzini et al. (2013) | Select the experts with the required skills for the specific submitted problem | Decision-making | Task Design |
| Tazzini et al. (2013) | Dynamic evaluation of individuals’ ability | Reasoning | Task Design |