For past few years, people are getting less and less tolerant of each
other. In India , this problem has got worse with some or other elections
around the year – when politicians engage in abusing one another , using foul
language .
About an year ago , this prompted me to send following blog ( by email )
to our Cabinet Ministers / State Chief Ministers , in which I proposed a “ Technology-based “ , solution as described below :
Ø Hate Speech : Prevention
Mechanism …………………….. 01 Dec 2023
Extract :
STEP A :
We
must prepare a list ( dataset ) of words / phrases , denoting hate .
This list will comprise words which have following connotations :
“
Racist / Sexist / Homophobic / Offensive / Dehumanizing / Trauma-causing /
Graphic / Violent / Profane / Swear words / Curses / Rude / Vulgar / Impolite
., etc “
As
per ChatGPT ( and also BARD ), these words would fall under following broad
categories :
1. Racist Language:
Specific racial slurs or derogatory terms targeting
particular ethnic groups.
2. Sexist Language:
Remarks or terms that discriminate against or belittle
individuals based on their gender.
3. Homophobic or Transphobic Language:
Derogatory comments or slurs aimed at individuals based on
their sexual orientation or gender identity.
4. Offensive or Dehumanizing Language:
Words that dehumanize or degrade individuals, treating
them as less than human.
5. Trauma-Inducing Language:
References to sensitive topics like abuse, violence, or
personal tragedies that could cause emotional distress.
6. Graphic or Violent Language:
Detailed descriptions of violent or gruesome scenarios
that might disturb or upset individuals.
7. Profanity, Swear Words, and
Curses:
Words or phrases considered vulgar, offensive, or socially
unacceptable in polite conversation.
8. Rude or Impolite Language:
Insensitive or disrespectful comments that undermine
courtesy or basic social norms.
9. Disinformation or
Misinformation:
False or misleading information, including conspiracy
theories or unverified claims presented as facts.
10. Threatening or
Aggressive Language:
Words or phrases that convey threats, aggression, or
intimidation towards individuals or groups.
STEP B :
Mandate all manufacturers of Mikes ( used in public gatherings ) to incorporate IoT
enabled SENSORS , having following capabilities :
# Capture entire speech and
convert it into text ( “ Speech to Text “ software are already commonplace )
# Transmit ( over internet ),
entire TEXT to a CENTRAL SERVER
STEP C :
Central Server will subject this text to
an AI based analysis .
Based on the presence of each “ Hate Word “ and its frequency and context of occurrence ,
AI will assign a rating to this text as follows :
1 ……………. Distasteful
2 ……………. Disrespectful
3……………….Offensive
4 …………….. Profane / Vulgar
5 ……………. Inciting violence /
Outright Hate
AI will :
# Immediately publish
its rating on the website > www.HatePrevent.gov.in
STEP D :
In all cases rated “ 3 / 4 / 5 “ , Server
will send “ instructions “ to the Mike-based SENSOR , to go MUTE
Such instructions could be sent even as the speech is proceeding !
Sure , implementation of this entire
suggestion, may take a few years to get implemented , even if agreed to by all
political parties / Election Commission / Supreme Court
I believe in harnessing technology (
Sensors – IoT – AI ) , since I believe humans
are unlikely to constrain themselves on their own
Now French AI startup MistralAI
have come up with a very similar suggestion , as follows :
“ MistralAI
takes on OpenAI with new moderation API , tackling harmful content in 11 languages
“
{ Venture Beat / 07
Nov 2024 }
Extract :
French artificial
intelligence startup Mistral AI launched
a new content moderation API on
Thursday, marking its latest move to compete with OpenAI and other AI leaders
while addressing growing concerns about AI safety and content filtering.
The new moderation service,
powered by a fine-tuned version of Mistral’s Ministral
8B model, is designed to detect
potentially harmful content across nine different categories, including
sexual content, hate speech, violence, dangerous activities, and personally
identifiable information. The API offers both raw text and conversational content analysis capabilities.
“Safety
plays a key role in making AI useful,” Mistral’s team said in announcing the
release. “At Mistral AI, we believe that system level guardrails are critical
to protecting downstream deployments.”
The launch comes at a crucial
time for the AI industry, as companies face mounting pressure to implement
stronger safeguards around their technology. Just last month, Mistral joined
other major AI companies in signing the UK AI Safety Summit accord,
pledging to develop AI responsibly.
The moderation API is already
being used in Mistral’s own Le
Chat platform and supports 11
languages, including Arabic, Chinese, English, French, German, Italian,
Japanese, Korean, Portuguese, Russian, and Spanish. This multilingual capability gives
Mistral an edge over some competitors whose moderation tools primarily focus on
English content.
“Over the past few months,
we’ve seen growing enthusiasm across the industry and research community for
new LLM-based moderation systems, which can
help make moderation more scalable and robust across applications,” the company
stated.
The company’s technical
approach also shows sophistication beyond its years. By training its moderation
model to understand conversational context rather
than just analyzing isolated text, Mistral has created a system that can
potentially catch subtle forms of harmful content that might slip through more
basic filters.
The moderation API is
available immediately through Mistral’s cloud platform, with pricing based on
usage. The company says it will continue to improve the system’s accuracy and
expand its capabilities based on customer feedback and evolving safety
requirements.
Mistral’s
move shows how quickly the AI landscape is changing. Just a year ago, the
Paris-based startup didn’t exist. Now it’s helping shape how enterprises think
about AI safety. In a field dominated by American tech giants, Mistral’s European
perspective on privacy and security might prove to be its greatest advantage.
In my 91 years of age , I have never heard politicians using as much “
abusive / corrosive / derogatory / insulting “ language as it is being used in
election rallies during past 12 months
I urge the Election Commission to become much more pro-active ( ala T N Sheshan
) and write to all political parties / Central Government / State Governments
and the Supreme Court , to consider my suggestion
With regards,
Hemen Parekh
www.My-Teacher.in
www.HemenParekh.ai / 12
Nov 2024
