Whether you need an essay for school, to compose an e-mail to your workgroup, or even a personal assistant, there is an easy to use AI platform waiting to assist.  Although AI may be too easy to use. Anyone with a pc and an internet connection can use and program an AI platform to perform any number of tasks, no coding or programming experience necessary. 

This year the use of AI has surged as never before.  The response to this utilization of AI technology spans the full gambit of those who say, “Wait, remember Skynet?” to those who say, “It’s about time I’m all in, 100%.”  No matter where you stand on the issue AI is not going away. 

Historically the scientific community has enthusiastically embraced new technology and this is true for laboratories today.  However, many in the scientific community are divided. Some say the brakes need to be applied to slow the process to evaluate and govern what can be done.  Others encourage free experimentation, insisting we will get the best results by letting AI work unrestricted.  

This has raised some very important questions:

What about the ethics of AI?  What ethical guidelines have been established for the use of AI in scientific laboratories?  Since AI changes so rapidly, how can any guidelines be kept current as it advances?

AI has been used to speed up research and productivity in labs.  Machine learning has reportedly contributed to the approval of certain vaccines faster than previously achievable.  The advantages seem to be endless.  The potential for advancement seems to be endless, but is the potential risk just as high?

The Association for the Advancement of Artificial Intelligence, (AAAI) and other agencies have called for the need to implement some sort of modified Hippocratic Oath “First, do no harm”.  What if the humans utilizing the AI are unethical and use the platforms in a questionable way?  Yes, we all have heard of the lab analyst or operator that was terminated because they “dry labbed” the numbers.  Or the lab managers that have ordered results be thrown out or not reported because they violated a DMR or permit. 

Most of us in the RMWQAA do not work in pharmaceutical and medical research labs, but the water and wastewater world could be affected as well.  Method detection limits (MDLs) and maximum contaminant levels (MCLs) are continuously being lowered.  Could the pressure to keep up with new guidelines and regulations cause the manufacturers of instruments and method developers to look to AI for solutions?  Will the technology adhere to industry standards of ethics and work?  Only time will reveal the answers to these and other questions.

Just for fun, I asked a popular platform the following question:

How can we meet new EPA MDL requirements for water analysis?

Here is the lengthy answer I received (Spoiler Alert: Nothing groundbreaking was revealed but AI did not recommend using AI):

Meeting the new Minimum Detectable Level (MDL) requirements for water analysis set by the U.S. Environmental Protection Agency (EPA) can be challenging but is crucial for ensuring the accuracy and reliability of water quality data. Here are steps and strategies to help you meet these requirements:

1.    Understand EPA MDL Requirements: Familiarize yourself with the specific MDL requirements outlined in EPA methods relevant to your water analysis. These requirements can vary depending on the method and the analyte being measured.

2.    Select Appropriate Analytical Techniques: Choose analytical techniques and instruments that are capable of achieving the desired MDLs. This might involve using more sensitive equipment or methods, such as high-performance liquid chromatography (HPLC), gas chromatography-mass spectrometry (GC-MS), or inductively coupled plasma-mass spectrometry (ICP-MS).

3.    Calibration and Quality Control: Ensure that your laboratory's calibration procedures are accurate and precise. Regularly calibrate instruments and verify their performance using certified standards. Implement stringent quality control procedures to monitor and maintain instrument performance.

4.    Sample Collection and Preservation: Proper sample collection and preservation are critical to obtaining accurate results. Follow EPA-prescribed procedures for sample collection, storage, and transportation to prevent contamination and degradation.

5.    Method Validation: Validate your chosen analytical method to demonstrate its accuracy, precision, and reliability. This typically involves running known standards and spiked samples to assess the method's performance.

6.    Instrument Maintenance and Upkeep: Regularly maintain and service your analytical instruments to ensure they operate at peak efficiency. Any equipment malfunction or deterioration can negatively impact MDLs.

7.    Staff Training and Competency: Ensure that your laboratory staff is well-trained and competent in the specific analytical methods they are using. Continuous training and skill development are essential.

8.    Use Certified Reference Materials (CRMs): Incorporate CRMs into your analysis process to verify the accuracy of your results. CRMs are standardized materials with known concentrations of target analytes.

9.    Blank and Matrix Spike Analysis: Include blank samples and matrix spike samples in your analysis to assess and correct for background contamination and matrix effects.

10. Data Quality Assessment: Regularly review and assess data quality. Identify and investigate outliers or unusual results promptly. Document all quality control measures and data quality assessments.

11. Participate in Proficiency Testing Programs: Enroll in proficiency testing programs or inter-laboratory comparison studies to evaluate your laboratory's performance against other laboratories. This can help identify areas for improvement.

12. Documentation and Reporting: Maintain thorough documentation of all procedures, methods, and quality control measures. Report your results accurately, including MDLs, in compliance with EPA guidelines.

13. Stay Updated: Keep abreast of changes in EPA methods and requirements. The EPA periodically updates its methods and regulations, so it's important to stay informed and adapt accordingly.

Meeting EPA MDL requirements for water analysis demands a commitment to high-quality analytical practices, rigorous quality control, and ongoing training and improvement. It's essential to ensure the accuracy and reliability of water quality data, which is vital for environmental protection and public health.

Adele Rucker is the RMWQAA President and an Analytical Chemist in South Platte Renew’s Laboratory.