This documents lists down the common concerns seen around usage of Generative AI services like OpenAI.

1. OpenAI APIs - Common Concerns
Generative AIs can be used to collect and analyze personal data. There are some
common concerns of enterprises while using the publicly hosted generative AI
services (e.g. by OpenAI). This document highlights some of them!
Author
Abhilasha Sinha
Sr Solution Architect (Generative AI)
https://www.linkedin.com/in/abhilasha-sinha-hyd/

2. Data Privacy
When using an API, data is transmitted
over the internet to a third-party server.
Even if the data is anonymized or
encrypted, there are concerns about
how the data is handled, stored, and
potentially accessed.

3. Compliance with Regulations
Different jurisdictions have varying laws
and regulations regarding data
protection (such as GDPR in Europe).
Ensuring that a third-party service
complies with all relevant laws is a
complex and daunting task. The
enterprises are not confident about how
OpenAI is handling them!

4. Intellectual Property
For businesses dealing with proprietary
information, there are fears that sharing
data with a third party (e.g. OpenAI)
could lead to unintentional leakage of
intellectual property.

5. Dependency on a Third Party
Relying on an external service means
trusting that they will maintain the same
level of service, pricing, and ethical
standards over time. Changes in any of
these areas could impact the users of
the service.

6. Potential Bias and Ethical Considerations
There are also concerns related to the
training data used by OpenAI and
potential biases or ethical
considerations in the models. Different
people demand different level of
transparency. The existing transparency
in these areas is not always sufficient for
all users.

7. Security Protocols
Though a company like OpenAI
employs robust security measures,
potential vulnerabilities or breaches
could still occur. For some
organizations, maintaining in-house
solutions feels like a more secure
option. They feel that their customers
will feel safer.

8. Customization and Control
Using an external API might limit the
ability to customize or have control over
specific aspects of the model or its
training. They are concerned about
explainability. That is where, some
organizations have preference to build
and maintain their own models to have
complete control over all aspects of its
operation.

9. Cost Considerations
Depending on the scale and usage, the
cost of using a cloud-based API can
become a significant factor. Some might
opt for in-house solutions to have better
control over the costs.

10. Public Perception
Finally, public perception and customer
trust also plays a crucial role. Some
customers might have their own
concerns about data privacy and
security, and knowing that a company is
using a third-party service might affect
their perception and trust in the brand.

11. Conclusion
This is just a sample list of observations that we have. While all these concerns
are valid and need appropriate attention, the good thing is that there are
solutions to each of these concerns!
According to us,
1. the data privacy and confidentiality is the top challenge
2. usage of the data by the service provider to train their future models is
another major concern.
I feel that OpenAI is trying their best to be clear on these two fronts and seem
to be committing to businesses that they are aware of these concerns and their
customers should feel comfortable!

12. Looking for Generative AI - Implementation?
Generative AI is changing the way we
think, work, and innovate. At
WalkingTree, we're harnessing this
power to create groundbreaking solutions
for ourselves and our clients. If you share
our passion for generative AI, let's
collaborate! Contact us today and let's
build the future together. Explore more by
visiting our Analytics and GenAI pages.