AI Ethics

In Artificial Intelligence Ethical Review, Excel, As An Ethical Review Decision-making Tool, Can Effectively Improve Review Efficiency And Accuracy

In Artificial Intelligence Ethical Review, Excel, As An Ethical Review Decision-making Tool, Can Effectively Improve Review Efficiency And Accuracy

In Artificial Intelligence Ethical Review, Excel, As An Ethical Review Decision-making Tool, Can Effectively Improve Review Efficiency And Accuracy

This article will provide ethical review decisions using Excel, solve specific problems, and explain the operation methods in detail.During the process of artificial intelligence ethics review, examiners need to evaluate multiple projects, including project compliance, potential risks, ethical impact, etc. As a powerful data processing tool, Excel can help examiners organize data, analyze metrics, and generate decision reports.Step 1: Open Excel and create a new workbook. Step 2: In, enter the relevant fields of the ethical review project, such as project name, category, risk level, etc. Step 3: Use the shortcut key

This article will provide ethical review decisions using Excel, solve specific problems, and explain the operation methods in detail.

1. Practical application scenarios

During the process of artificial intelligence ethics review, examiners need to evaluate multiple projects, including project compliance, potential risks, ethical impact, etc. As a powerful data processing tool, Excel can help examiners organize data, analyze metrics, and generate decision reports.

2. Operation method

Data sorting

Step 1: Open Excel and create a new workbook. Step 2: In, enter the relevant fields of the ethical review project, such as project name, category, risk level, etc. Step 3: Use the shortcut key "Ctrl T" to create a table for easier subsequent data processing.

Data Filtering

Step 1: Select the data area and click the "Filter" button under the "Start" tab. Step 2: Set filtering conditions according to your needs, such as filtering out items with a risk level of "high".

Conditional Format

Step 1: Select the cell area that needs to be formatted in conditional. Step 2: Click the "Conditional Format" button under the "Start" tab and select "New Rule". Step 3: Set the conditional format, such as setting the background color of the cell with a risk level "High" to red.

Data Analysis

Step 1: Use Excel formula to calculate the comprehensive score of each item. For example, use the SUM function to calculate the sum of the scores of each term. Step 2: Use the pivot table to analyze the distribution of each project category and risk level.

3. VBA code and Excel formula

VBA code

The following code is used to automatically filter items with a risk level of "high":

vba

copy

Sub Filter high-risk items ()

Dim ws As

Set ws = .("")

'Set filter conditions

ws.Range("A1:D1"). Field:=3, :="High"

Artificial Intelligence Ethics_What is Artificial Intelligence Ethics_Definition of Ethics

.Frozen the first line

ws.

ws.Rows("1:1").

. = True

End Sub

Excel formula

The following formula is used to calculate the comprehensive score of the item:

excel

copy

=SUM(B2:D2)

Formula parameter description:

B2:D2: represents the cell area where the sum of the scores needs to be calculated.

4. Usage tips and precautions

Usage Tips

During the data sorting stage, you can make full use of the data verification function to ensure the accuracy of the input data.

During the data analysis stage, the data distribution can be displayed more intuitively with the chart function.

Things to note

When using VBA code, make sure the Development Tools tab is enabled.

When setting conditional formatting, avoid too many conditions, which causes Excel to run slowly.

5. Applicable conditions and limitations of codes and formulas

VBA code

Applicable conditions: Applicable to Excel 2007 and above.

Limitations: A certain degree of VBA programming knowledge is required.

Excel formula

Applicable conditions: Applicable to all Excel versions.

Limitations: The calculation results are limited by the accuracy of the data source.

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