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(CNN) – Artificial intelligence doesn't know what to make of Os Keyes.

The 29-year-old graduate student is dark-haired, tattooed and openly transgender, using the pronouns 'they' or 'them.' Facial analysis software, however, typically assigns each face it analyzes one of two labels: male or female.

The software literally can't categorize Keyes correctly.

Yet for Keyes, who studies gender, technology and power at the University of Washington, this technology is not simply software that doesn't get it right. According to them, it's also representative of how companies are not thinking through how power is distributed and norms are reinforced by such software. And Keyes — like a number of other experts in AI and in gender issues who spoke with CNN Business — is concerned about how these AI classifications could police, restrict, or otherwise harm transgender people, as well as those who don't look stereotypically male or female.

Braina enables you to do belongings you do every day. It is a multi-functional synthetic. Build Your Own AI (Artificial Intelligence) Assistant 101: Remember the time, when you were watching Iron Man and wondered to yourself, how cool it would be if you had your own J.A.R.V.I.S? Well, It's time to make that dream into a reality. Artificial intelligence. Watson is an IBM supercomputer which is one of the best artificial intelligence software for pc that combines artificial intelligence (AI) and it is also a sophisticated analytical software to optimize the performance. Features: Supports distributed computing. It runs smoothly with the existing tools. Provides an API for application development. (CNN) – Artificial intelligence doesn't know what to make of Os Keyes. The 29-year-old graduate student is dark-haired, tattooed and openly transgender, using the pronouns 'they' or 'them.

'The people producing this software are producing something that, in a small way, makes people like me miserable and keeps us miserable,' Keyes told CNN Business.

Top tech companies including Microsoft, Amazon and, until recently, IBM, have all invested in technology that can tag pictures of faces fed to their AI systems with binary labels such as 'male' and 'female,' along with predicting other characteristics, such as whether they are wearing glasses or makeup. A company might, as Amazon suggests in a company blog post, use this gender-prediction feature to analyze footage of shoppers at their stores to learn about how many are men and how many are women. The technology is often offered alongside facial recognition software, though they may be separate systems.

But there is a fatal flaw: The way a computer sees gender isn't always the same way people see it. A growing number of terms for describing one's gender are becoming common in everyday life. Over a dozen states and Washington, DC, currently or will soon offer a third gender option, 'X,' on drivers' licenses. Companies such as United Airlines now let customers pick the pronoun 'X' or the gender-neutral honorific 'Mx' when booking a ticket. On Instagram, 9 million posts are tagged as 'transgender' and over 7 million as 'trans.' Well over 3 million posts are tagged with the hashtag 'nonbinary.' Gender diversity is on smartphones, too, as both Apple and Google offer nonbinary emoji.

As these societal changes proliferate, AI-driven conclusions have become more than a gender identity concern. Some AI experts and members of the transgender community are worried about the potential for serious repercussions if gender recognition, as it exists today, is put to use for more complicated and sensitive tasks, whether it be using AI to help screen job candidates or nab criminal suspects.

Keyes is personally afraid it could enable a surveillance system to issue alerts when someone of the 'wrong gender' walks into a bathroom or changing room. Indeed, one AI startup told CNN Business that it offers a gender prediction system that could help security guards flag men who are in an all-female dormitory, or vice versa.

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'What you're talking about is deliberately putting trans people, who don't have the best relationship with law enforcement, on a collision course with law enforcement,' Keyes said.

Already, AI that scans your face is being used for security applications at concerts, airports, sports arenas and more. These sensitive use cases only raise the stakes for how peoples' lives could be upended by a few lines of code.

'I think we need to push back on the idea that these systems should exist at all, and look at these kind of assumptions — that someone's body or face or style or hair can kind of detect their interior state or identity,' said Meredith Whittaker, a former Google employee and cofounder of New York University's AI Now Institute, which studies social impacts of AI.

Tech (mostly) doesn't want to talk about it

The tech companies are mostly staying quiet on these concerns. Amazon and Microsoft declined to comment for this story. IBM, which appeared to stop offering facial-analysis services in September, also declined to comment. Kairos and Megvii, both AI startups that offer such services, didn't respond to requests for comment. (Google, which offers image-identification features through its Cloud Vision service, doesn't appear to offer a gender-labeling feature as part of its facial analysis tools, but the company declined to confirm whether or not this is the case.)

Only one company contacted by CNN Business, New York-based startup Clarifai, was willing to speak. Kyle Martinowich, VP of commercial sales and marketing, said Clarifai built its AI model for predicting gender in response to customer demand. He said those customers now range from bricks-and-mortar stores — who may use Clarifai's technology to figure out how many women walk down a particular aisle — to the US government — which may use it for gathering information about the types of people walking through airports or into federal buildings.

Clarifai's system for recognizing gender was trained on a data set of over 30 million images, each of which was annotated as masculine or feminine by three different people. Given how small the trans population is — an estimated 1.4 million adults in the US alone, or 0.6% of the adult population — there's no training data available to help the company incorporate trans individuals into its gender predictions, according to Martinowich. And he argued it's not worth the money it would cost to source such data. But if a customer offered to pay the company to make such a product, and brought its own data, he said Clarifai would comply.

Martinowich stressed there are limits to what Clarifai would allow customers to do with its services. For instance, he said that 'if the Congolese government called us and said, 'We want to stop females from entering an all-male building,' we wouldn't sell them that. And if we found out, we would cut our service off to them.'

Yet, he also said Clarifai is talking to companies that offer single-sex dormitories about how the startup's automated gender-identification could be used for safety and security purposes — not to deny someone entry to a building, but to flag a security guard 'who would need to make the human determination' about whether a person should be rejected from a building.

How well does the technology work?

The automated facial analysis systems used by tech companies invariably compute gender as one of two groups — male or female. This may come with a numerical score indicating how confident the computer is that the face it sees looks like one gender or the other.

Yet a small but growing area of research indicates there are a number of issues with using AI to spot gender, such as increased error rates when it comes to identifying women of color and concerns about accuracy in general.

There's also the question of how well the technology works when it encounters pictures of people that identify themselves differently than the software might. As Morgan Klaus Scheuerman, a graduate student at the University of Colorado Boulder, found in a recent study, facial analysis systems from major tech companies were all markedly worse at determining gender when confronted with images of people who are trans.

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Scheuerman and other researchers built a dataset of 2,450 photos of faces from Instagram that had been labeled by their authors with one of seven different gender-related hashtags such as 'transman', 'transwoman', 'man', 'woman' and 'nonbinary.' Then they ran the images through facial-analysis services from Microsoft, Amazon, IBM, and Clarifai.

The results? On average, the services classified photos tagged 'woman' as 'female' 98.3% of the time, and photos tagged 'man' as 'male' 97.6% of the time.

When it came to images tagged 'transwoman' or 'transman', however, they fared far worse. Photos with the 'transwoman' tag were identified as 'female' over 87.3% of the time, but photos tagged as 'transman' were labeled as 'male' just 70.5% of the time. Amazon did most poorly when it came to labeling 'transman'-tagged photos as male, which it did just 61.7% of the time.

Scheuerman said this may indicate that images of trans men are not included in training these AI systems to determine what men look like.

'I think the real danger is this notion of objectivity,' said Scheuerman, a long-haired, facial-piercing-bedecked student who studies gender and technology and has repeatedly been misidentified by these systems. 'The idea that because this is trained, this system is super advanced, then it must be making these objective,Any time you try to codify gender norms, either into laws or into algorithms, you're bound to have an impact on anyone who's not Ron Swanson or Barbie,' she said.

To make matters more complicated, companies are already using commercially available AI to deduce gender for a number of reasons — and they're not always using it in the ways the creators intended.

For instance, Amazon writes in its online Rekognition developer guide that gender predictions from its facial analysis service are 'not designed to categorize a person's gender identity' and shouldn't be used to do so. (According to the version of the developer guide that Amazon maintains on Github, this kind of language was added in late September; previously, it included no guidance about how the technology was intended to be used.)

Yet Woo, an Indian dating app that matches heterosexual couples, uses Rekognition's gender-identifying feature mainly to help make sure the gender that users state in their profile matches up with the images of themselves they post within the app, said Woo cofounder and CEO Sumesh Menon.

If there's a perceived mismatch, a human worker will be notified, and they may contact the user to ask if their gender is incorrectly stated in the app, Menon said. Men, for instance, have accidentally labeled themselves as women in the past, then complained that they were only seeing other men as potential matches.

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'It's not very nuanced; it's very straightforward,' he said. 'But it is super helpful in how we are able to present profiles to the right gender.'

However, it shows that companies selling this AI technology can't control its deployment once it's in the hands of customers. (Woo is listed, along with a testimonial from Menon, on an Amazon Rekognition Customers page.)

'That's in a way proving the point that there's no way to really ensure your client is using this in an ethical way or a way you intended it to be used,' said Scheuerman.

Nix it, or fix it?

Despite the ethical concerns, businesses believe there is a clear value in having this gender data — but only if the data itself is accurate. To that end, rather than abandon the feature, some companies are now wrestling with how to improve its predictive capabilities.

Limbik, a startup that calls itself a 'data studio for short-form video,' uses AI to analyze videos and predict what people will want to watch. The startup turns to AI from Amazon and IBM to identify gender in videos and analyze all manner of things, such as how frequently men pop up in a certain kind of commercial.

But Limbik CEO Zach Schwitzky said his company has 'struggled with binary classification.' Two common issues he encounters with the software include short-haired females being classified as males, and people who appear to be teenagers being misclassified as either gender. In his experience, existing automated gender identification works well for anyone who's between 25 and 35, but that it's not as helpful for people who are older or younger.

Now, Limbik is building its own software to label gender in images, which to start includes three categories: male, female, and other. Eventually, the company may add more categories, too. Right now, the company is sorting images by hand from sites like Facebook, Twitter, Instagram; these will be used to train an AI model, Schwitzky said.

'I just struggle to think about how to do it in a way that it could be done accurately and effectively,' Schwitzky said.

The research community, too, is wrestling with how to represent gender. Aaron Smith, director of Data Labs at Pew Research Center, said the issue of how to accurately represent gender and gender identity 'is a topic of huge interest,' particularly to those who study AI.

Yet whether AI can be built that could accurately identify gender on a broader spectrum, or perhaps consider any characteristics beyond outward appearances, is still largely unknown.

Smith isn't sure whether technology will eventually be able to suss out a person's internal identity. He notes that that identity can be 'inherently opaque' to AI systems making assessments based on outward appearances.

For those like Keyes, who are worried about the consequences of using AI to recognize gender, there's a belief that no amount of tinkering will make these systems work or even worthwhile.

'You could add a million categories, and unless you're adding one category per person you're never going to get to a place where you can work out someone's gender from their face,' Keyes said.

This story was first published on CNN.com, 'AI software defines people as male or female. That's a problem'

Artificial Intelligence (AI) software is a computer program that imitates human activities and behavior by learning various data patterns and insights, therefore, a combo of AI with machine makes to day to day life much simpler and easier. AI software plays a vital role in transforming anything from scratch to a valuable document. It not only simplifies apps but also streamlines the same according to its usability. Let’s discuss the best Artificial Intelligence Software for PC.

Features of AI

  1. Artificial Intelligence Platforms: This will provide the platform for developing an application from scratch and therefore many built-in algorithms are provided in this. Drag and drop facility makes it easy to use.
  2. Chatbox: This software is mostly used in most of the leading companies. It automates the conversation. AI software replies to the chat and therefore in the nutshell AI generates the chatbox and responds on behalf of the company. Matrimonial portals use the chatbox.
  3. Deep Learning Software: It is comprised of speech recognition, image recognition, etc.

Now let us throw some lightson Best Artificial Intelligence Software for PC

1) Google Cloud Machine Learning Engine

Google Cloud Machine Learning Engine helps you in training your model. Components that are provided by Cloud ML Engine are Google Cloud Platform Console, gcloud, and also REST API.

Features:

  • Google Cloud helps in training, analyzing and fine-tuning the model.
  • This trained model will then get deployed
  • Then it will start forecasting, one has to monitor those fore castings and will also be able to manage your models and its versions.
  • Google Cloud ML has 3 components, i.e. Google Cloud Platform Console is a UI interface for deploying models & managing these models, versions, & jobs; gcloud is a command-line tool for managing the models and versions, and REST API is for online predictions.

Tool Cost/ Plan details: The cost of training varies in different countries.

  • US: $0.49/hour for per training unit.
  • Europe: $0.54/hour for per training unit.
  • The Asia Pacific: $0.54/hour for per training unit.

2) Azure Machine Learning Studio

Azure Machine Learning Studio is a combined, drag-and-drop tool. It can be used to build predictive analytics solutions on data, therefore, Machine Learning Studio publishes models as web services also.

Features:

  • It can deploy the models in cloud and on-premises and also at the edge.
  • Provides a user-based solution.
  • Simple and easy to use because of its drag and drop feature.
  • It is scalable.
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Tool Cost/ Plan details: Anyone can generate a freeaccount. He will be privileged with more than 25 services with one account. Ifrequired, it can be upgraded at any time by paying additional charges.

3) TensorFlow

It is the latest and widely used apps of the AI and therefore the mostfamous profound learning library in the world is Google’s TensorFlow. If theuser types a keyword at the search bar then Google provides a recommendationabout what could be the next word.

Features:

The solution can be used on:

  • CPUs, GPUs, and TPUs.
  • Desktops
  • Clusters
  • Mobiles
  • Edge devices

Tool Cost/ Plan details: Free of cost.

4) H2O.AI

It is used by more than 129,000 data scientists and 12,000 organizationsglobally. Now a day it is widely used by the banking, insurance, healthcare,marketing, and telecom sector and therefore

This tool allows a user to use programming languages like R and Python tobuild models and also open-source machine learning tool can be useful foreveryone.

Features:

  • Auto ML function
  • Supports most of the algorithms like gradient boosted machines, generalized linear models and also deep learning.
  • Linearly scalable platform.
  • It follows a distributed in-memory structure.

Tool Cost/ Plan details: Free of cost

5) Cortana


It provides a virtual assistant, helps by multi-tasking like setting an alarmor reminders, answering your questions, etc. and it also Supports operatingsystems include Windows, iOS(Siri) Android, Amazon fire stick (Alexa) and XboxOS.

Features:

  • It is multi-tasking; – it assists right from placing an order for a pizza to switching on the light.
  • Uses the Bing search engine.
  • It follows a voice command.
  • Supported languages include English, Portuguese, French, German, Italian, Spanish, Chinese, and also Japanese.

Tool Cost/ Plan details: Free of cost.

6) IBM Watson

Watson is an IBM supercomputer which is one of the best artificial intelligence software for pc that combines artificial intelligence (AI) and it is also a sophisticated analytical software to optimize the performance.

Features:

  • Supports distributed computing.
  • It runs smoothly with the existing tools.
  • Provides an API for application development.
  • It can be executed from small data also.

Tool Cost/ Plan details: Free of cost

7) Salesforce Einstein

We usually have data and therefore Salesforce Einstein learns from all that data to deliver predictions and recommendations based on the unique business processes and it pairs that with automation and the user has the insights and time to truly connect with his customers.

The bottom line is that it is a Customer Relationship Management (CRM)system. This can be applied to Sales, Marketing, Community, Analytics, andCommerce.

Features:

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  • Provides more awareness about the opportunities.
  • Derives data and manages the time of data entry by adding new contacts.
  • Helps in prioritizing the opportunities based on history.

Tool Cost/ Plan details: Salesforce provides a 30-day freetrial. For further inquiry contact their customer care service.

8) Infosys Nia

Infosys Nia will help the enterprises by making tough tasks into simpler ones and it also has three components like Data platform, Knowledge platform, and also automation platform.

Features:

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  • It helps in refining the systems and processes, to empower the business.
  • Provides automation also for repetitive and also programmatic tasks.
  • Automation platform blends RPA, Predictive automation, and also Cognitive automation.
  • Knowledge platform is all about capturing, processing and also reusing the knowledge.
  • Data platform provides advanced data analytics and also machine learning platform.

Tool Cost/ Plan details: Get in touch with them for pricingdetails

9) Amazon Alexa

It is just like Cortana as it understands English, French, German, Japanese,Italian, and Spanish.

Features:

  • API is provided to support development.
  • It can be upgraded with the current products also using AVS (Alexa Voice Service).
  • Based on cloud service.
  • It can connect to devices like Camera, lights, and also entertainment systems.

.

Tool Cost/ Plan details: Free with some amazon devicesor services.

10) Google Assistant

It is a voice assistant by Google and therefore nowadays it is widely usedon mobiles and smart home devices. Operating systems that are supported includeAndroid, iOS, and KaiOS and also

Languages that Google Assistant Supports are English, Hindi, Indonesian, French, German, Italian, Japanese, Korean, Portuguese, Spanish, Dutch, Russian, and also Swedish.

Features:

Functions which Google Assistant can do are:

  • Supports two-way conversation and also schedules events.
  • Search for the information on the internet.
  • Sets alarms.
  • It identifies objects, songs, and can also read visual information.

Tool Cost/ Plan details: Free of cost. It can bedownloaded or installed from the play store.

Conclusion

Thus to conclude, an artificial intelligence once restricted to science and the movies, today’s Artificial Intelligence is in your pocket, on your computer and coming soon to a variety of devices and technologies that you can also use every day. What actually best artificial intelligence software for pc is? The term itself was coin by Dartmouth College’s John McCarthy in 1955 in a proposal to university researchers for its summer research project on AI. According to the cognitive scientist Marvin Minsky, one of the field’s most famous practitioners, AI is “the science of making machines do things that would require intelligence if done by men.” Practically, artificial intelligence – also simply defined as AI – has come to represent the broad category of methodologies that teach a computer to perform tasks as an “intelligent” person would.

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