There are commercial IRBs whose review services can be purchased, and included in the study budget.. NIJ does not endorse any particular commercial IRB. There may be local universities that might agree to partner for IRB review, if the applicant organization has a relationship with the university. All IRBs reviewing DOJ-funded research must be informed that the DOJ human subjects protection regulation at 28 CFR Part 46 (pre-2018 Common Rule) should be used to review the IRB application.
No, the only exemptions in 46.101(b) are 1-4 that can be used to exempt DOJ-funded research if the study meets any of the listed criteria. B5 and B6 exemptions are not applicable to DOJ-funded research. B5 for public service benefit/service programs refers to programs that provide a monetary benefit to recipients, such as Food Stamps (SNAP Food Benefits) Welfare or Temporary Assistance for Needy Families (TANF) Medicaid and Children's Health Insurance Program (CHIP).
An application is not required to contain complete IRB approved documentation, rather the human subjects form required with applications Protection of Human Subjects Assurance Identification/IRB Certification/Declaration of Exemption (Common Rule) in box 6 can indicate that IRB review is forthcoming. Once an award is made, no work may begin until NIJ has approved the submitted IRB documentation and has released funds.
If an application is awarded, it is the responsibility of the awardee to submit human subjects protection and privacy documentation. If the sub-awardee is conducting research on behalf of the awardee, then the sub-awardee can submit the documentation provided the awardee has a reliance agreement with the sub. If both are conducting research, they can agree, again using a reliance agreement, to use a single IRB. If they cannot agree or wish to have both the awardee’s IRB and the sub’s IRB review the study, then both IRBs will need to provide consistent but separate IRB documentation. The human subjects regulation that applies to NIJ-funded awards is 28 CFR Part 46 (pre-2018 Common Rule), which should be used by IRBs to review NIJ-funded protocols and cited in IRB determination letters.
Each successful applicant (i.e., the host academic institution) may request up to $60,000 per year for up to three years of support (for a maximum total of $180,000).
Each year of support includes:
- $41,000 for the fellow’s Salary and Fringe
- up to $16,000 for Cost of Education Allowance
- up to $3,000 for Research Expenses
Students should work with their university Office of Sponsored Programs (OSP) representative to prepare the budget. Applicants are encouraged to consult the Budget Preparation and Submission Information section of the Grant Application Resource Guide for guidance.
The Budget Webform must be submitted with the application and must clearly show a breakdown of all costs associated with every allowable budget category. All proposed expenses must comply with the DOJ Financial Guide and be justified and explained in the Budget Worksheet and Narrative.
Each year of support includes $41,000 for the fellow’s salary and fringe or health insurance. Where possible in accordance with institutional policy, the university should account for the full $41,000 when requesting the personnel expenses of the doctoral student. If the applicant elects not to request the full $41,000 for salary, fringe or health insurance, the remaining funds may not be used for any other purpose or transferred for use under another programmatic budget category.
Up to $16,000 annually may be requested as a Cost of Education Allowance. This may include tuition, fees, and university administrative or indirect costs.
In addition, up to $3,000 annually may be requested under the Research Expenses allowance. This can include research supplies, instrumental user facility time, compensation for human subjects, undergraduate research assistants, data collection site travel, conference travel, or professional society membership fees, among other allowable expenses.
If the university elects not to use the entire $16,000 Cost of Education Allowance for tuition, fees, or administrative or indirect costs, the remaining portion may be used to supplement allowable expenses under the Research Expenses category. In that case, total Research Expenses may exceed $3,000.
For more information on allowable expenses, see the DOJ Financial Guide.
The end date of the project should be a reasonable estimate for the date of acceptance of the student's successfully defended dissertation. The end date may assume a total period of up to five years, but only three full years of fellowship funding will be possible during that period.
Yes, indirect costs are allowed under the Cost of Education Allowance.
AI is a rapidly advancing field of computer science. In the mid-1950s, John McCarthy, who has been credited as the father of AI, defined it as “the science and engineering of making intelligent machines."[1] Conceptually, AI is the ability of a machine to perceive and respond to its environment independently and perform tasks that would typically require human intelligence and decision-making processes, but without direct human intervention. One facet of human intelligence is the ability to learn from experience. Machine learning is an application of AI that mimics this ability and enables machines and their software to learn from experience.[2] Particularly important from the criminal justice perspective is pattern recognition. Humans are efficient at recognizing patterns and, through experience, we learn to differentiate objects, people, complex human emotions, information, and conditions on a daily basis. AI seeks to replicate this human capability in software algorithms and computer hardware. For example, self-learning algorithms use data sets to understand how to identify people based on their images, complete intricate computational and robotics tasks, understand purchasing habits and patterns online, detect medical conditions from complex radiological scans, and make stock market predictions.
[note 1] “What is Artificial Intelligence,” The Society for the Study of Artificial Intelligence and Simulation of Behaviour.
[note 2] Bernard Marr, “What Is the Difference Between Deep Learning, Machine Learning and AI?” Forbes (December 8, 2016).
Just like humans, learning is a matter of classification and patterns. AI is said to learn through supervised, unsupervised, and semi supervised and reinforcement learning. In supervised learning, AI algorithms are trained by using large numbers of labeled examples. Unsupervised AI algorithms strive to identify patterns in data, looking for similarities that can be used to categorize the data without the aid of labels. Semisupervised learning uses a small amount of labeled data to learn to classify a larger set of unlabeled data. Approach is useful when extracting features from data is difficult, and labeling examples is a time-intensive task for experts. Reinforcement learning trains an algorithm with a reward system, providing feedback when an artificial intelligence agent performs the best action in a particular situation. In reinforcement learning, the system attempts to is going through a process of trial and error until it arrives at the best possible outcome to find the optimal way to complete a particular goal, or improve performance on a specific task.
Adapted from What is AI? Everything you need to know about Artificial Intelligence and SuperVize Me: What’s the Difference Between Supervised, Unsupervised, Semi-Supervised and Reinforcement Learning?
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