ARMONK, N.Y., Sept. 19, 2018
/PRNewswire/ -- IBM (NYSE: IBM) today introduced technology that
gives businesses new transparency into AI, enabling them to more
fully harness its power.
The software service, which automatically detects bias and
explains how AI makes decisions – as the decisions are being made –
runs on the IBM Cloud, and helps organizations manage AI systems
from a wide variety of industry players. IBM Services will also
work with businesses to help them harness the new software
service.
In addition, IBM Research will release into the open source
community an AI bias detection and mitigation toolkit, bringing
forward tools and education to encourage global collaboration
around addressing bias in AI.
"IBM led the industry in establishing Trust and Transparency
principles for the development of new AI technologies," said
Beth Smith, General Manager of
Watson AI at IBM. "It's time to translate principles into practice.
We are giving new transparency and control to the businesses who
use AI and face the most potential risk from any flawed decision
making."
These developments come on the back of new research by IBM's
Institute for Business Value, which reveals that while 82 percent
of enterprises are considering AI deployments, 60 percent fear
liability issues and 63 percent lack the in-house talent to
confidently manage the technology.
Visibility into AI decisions
IBM's new Trust and Transparency capabilities on the IBM Cloud
work with models built from a wide variety of machine learning
frameworks and AI-build environments such as Watson, Tensorflow,
SparkML, AWS SageMaker, and AzureML. This means organizations can
take advantage of these new controls for most of the popular AI
frameworks used by enterprises.
The software service can also be programmed to monitor the
unique decision factors of any business workflow, enabling it to be
customized to the specific organizational use.
The fully automated software service explains decision-making
and detects bias in AI models at runtime – as decisions are being
made – capturing potentially unfair outcomes as they occur.
Importantly, it also automatically recommends data to add to the
model to help mitigate any bias it has detected.
Explanations are provided in easy to understand terms, showing
which factors weighted the decision in one direction vs. another,
the confidence in the recommendation, and the factors behind that
confidence. Also, the records of the model's accuracy, performance
and fairness, and the lineage of the AI systems, are easily traced
and recalled for customer service, regulatory or compliance reasons
– such as GDPR compliance.
All of these capabilities are accessed through visual
dashboards, giving business users an unparalleled ability to
understand, explain and manage AI-led decisions, and reducing
dependency on specialized AI skills.
IBM is also making available new consulting services to help
companies design business processes and human-AI interfaces to
further minimize the impact of bias in decision
making.
Empowering the open source community to build fairer
AI
In addition, IBM Research is making available to the open
source community the AI Fairness 360 toolkit – a library of novel
algorithms, code, and tutorials that will give academics,
researchers, and data scientists tools and knowledge to integrate
bias detection as they build and deploy machine learning models.
While other open-source resources have focused solely on checking
for bias in training data, the IBM AI Fairness 360 toolkit created
by IBM Research will help check for and mitigate bias in AI models.
It invites the global open source community to work together to
advance the science and make it easier to address bias in AI. You
can read more in a blog here.
Study reveals priorities and hurdles for mainstream AI
deployment
According to IBM's just-released study of 5,000
C-Suite executives, the IBM Institute for Business Value AI 2018
Report, there is a significant shift underway in how business
leaders look at AI's potential to drive business value and revenue
growth.
Among the key findings:
- 82% of enterprises, and 93% of high-performing enterprises, are
now considering or moving ahead with AI adoption with a focus on
revenue generation.
- 60% fear liability issues and 63% lack the skills to harness
AI's potential.
- CEO's perceive the greatest value in AI adoption to be in IT,
information security, innovation, customer service, and risk
management.
- AI adoption is higher and likely to accelerate faster in more
digitized industries like financial services.
About IBM & Artificial Intelligence
A world leader
in AI software, services, and technology for business, IBM has
deployed Watson AI solutions in thousands of engagements with
clients across 20 industries and 80 countries. IBM's Watson AI
solutions are widely used in industries, including by seven of the
10 largest automotive companies and 8 of the 10 largest oil and gas
companies.
Media Contact(s):
Caitlin
Leddy
IBM Media Relations
+ 1-646-880-7599
Caitlin.leddy@ibm.com
Hanna Smigala
IBM Media Relations
+1-203-512-5497
Smigala@us.ibm.com
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SOURCE IBM