Great Expectations Ethical AI Expectations
A collection of Expectations to validate for degradation, bias, and related Ethical Data concerns with Great Expectations.
What Is Ethical Data / Ethical AI and Why Is It Important?
The buzz around ethical AI has been growing louder and louder. Companies are collecting and using more data than ever before. And the influence of that data is growing just as fast—with data powering decisions and actions across every industry.
It's critical that the algorithms fueling these decisions and actions are ethical ones. That's where ethical AI comes in. Ethical AI is artificial intelligence that adheres to strict guidelines (or codes of conduct) regarding fundamental values to ensure automated systems respond to situations in an ethical way. For example, an algorithm that determines credit limits shouldn't discriminate against women by granting them lower limits.
How Can Great Expectations Contribute to Ethical AI
Great Expectations facilitates ethical AI by making it faster and easier to turn codes of conduct into actual code that can be quickly applied to data. For example, one common source of bad model performance is degradation in accuracy over time. For example, an Expectation like expect_column_label_and_predicted_pair_accuracy_to_be_between could be used to guard against model degradation.
Author: Great Expectations
Metadata
Release files for great-expectations-ethical-ai-expectations 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| great_expectations_ethical_ai_expectations-0.1.0.tar.gz | 11.8 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| great_expectations_ethical_ai_expectations-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 26.0 kB
Release files / great_expectations_ethical_ai_expectations-0.1.0.tar.gz
| Download URL | great_expectations_ethical_ai_expectations-0.1.0.tar.gz |
|---|---|
| Size | 11.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
83e7611d62ad443838105ffce7147400c0fbce165f790df0e8ee616f3c22c2ba
|
|
BLAKE2b-256 checksum How to use checksums |
d5b7684468ecc0fe8425c8ffed7cb287797de633a2e7063ffb464ec57ccdddeb
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.9.16
|
Release files / great_expectations_ethical_ai_expectations-0.1.0-py3-none-any.whl
| Download URL | great_expectations_ethical_ai_expectations-0.1.0-py3-none-any.whl |
|---|---|
| Size | 14.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
eaf96663dbd7d6bb485068379ecdb21c3275e360d95bc727cce4c675af09297b
|
|
BLAKE2b-256 checksum How to use checksums |
c1f1c7aa4187fe4920e708ab8bb0580c74f0087eac8910b149be89537cd356e7
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.9.16
|
Security for great-expectations-ethical-ai-expectations 0.1.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.