AI and data protection - balancing tensions

| August 13, 2019

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Artificial intelligence (AI) has “the potential to transform our world, from improving healthcare, reducing energy consumption and predicting climate change to credit scoring and fraud detection” . At a more commercial level, it can help organisations to profile, interact with, and sell to, their customers (see box “What is artificial intelligence?”.As AI becomes ever more popular, organisations are starting to grapple with the reality of how to balance AI design and deployment with data protection compliance. At the same time, regulators and governments are faced with their own AI balancing act: ensuring the safe and ethical deployment of AI without stifling innovation.

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FirstAlign enables you, your team, and your organization to lead with targeted tools supported by a creative, seasoned group of professionals, from diverse disciplines and the Artificial Intelligence space. We work across major industry sectors, public companies, fortune 2000 and government authorities, utilizing startup mindsets in making complexity simple.

OTHER ARTICLES

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Effects of Artificial Intelligence on Software Development

Article | June 8, 2021

What’s the core of those drone-supported Amazon deliveries, online food orders, the ability to watch your favorite shows on Netflix, and virtually augmented monitoring of your upcoming trip to Disneyland? Software! They constitute a significant part of almost every evolution we see around us. But how are the developers managing to yield so much from computer programming? How are they able to enrich so many lives through their creations all over the world? The answer is simple — Artificial intelligence (AI). Undoubtedly, AI is one of the leading technologies now, and it has the power to transform every bit of any business’ functionality. The software industry is not behind in making the most of AI and delivering intelligent and intelligent software. On the contrary, modern enterprises are convinced to adopt an entirely new software development paradigm to stand out from the competition. Traditionally, machine learning was predominant in the Software Development Lifecycle (SLDC). Even though it could encode numerous tasks in a computer program, it took relatively more time to be finalized. It required developers to put the exact requirements together first and hand them over to engineers. And then, engineers programmed the code accordingly. However, AI came with its advantages. As a result, it is reshaping the modern world of automated testing, Agile test software, and ultimately the entire software development. So if you see bots accompanying computer programs to make software development even easier, faster, and smarter in the future, it will be because of AI. So if you are already thinking of potential changes AI will bring to your software development process and how you can reap all the benefits of AI software development, stay tuned! Area of AI Software Development Artificial intelligence has a significant impact on various aspects of software development, for example, software testing, coding, designs, etc. Let’s now discuss what role AI will play in the current and future of software technologies by reshaping the major software development areas. Software Design Process will Improve Designing software is one of the most complicated and error-prone stages of software development. Therefore, specialized skills and the right experience are crucial for designing and planning software development projects to come up with an absolute solution. Moreover, the software designs are mostly subjected to dynamic changes as clients may suggest changes in different stages of software development. AI-powered systems such as AIDA (Artificial Intelligence Design Assistant) can eliminate such complexities in the design process. Time & Money Saving Software Testing Traditionally, software testing takes a lot of time, especially when there are changes in the source code. Plus, it's costly, too! But in the end, it’s one of the essential software development stages as it ensures product quality. Therefore, there’s no room for error. Thankfully, there’s AI and a variety of software testing tools. Testers can utilize them to develop test cases and carry out regression testing. This kind of automated testing is relatively faster, smarter, and astonishingly time and money-saving. On top of all, it's error-free! Easy Data Gathering and Analysis Data gathering and data analysis are the most fundamental stage of any software development lifecycle and need a significant amount of human intervention. The project team has to come up with all the information necessary for the software development, and clients' input can be dynamic. Automated data gathering through various AI tools such as Google ML Kit can be the best option to ease the process. It can take care of specific data-gathering processes without the need for significant human intervention. Say Bye to Manual Code Generation Generating huge codes requires a lot of labor, time, and money. Therefore, simplifying the code generation process is significant because code writing is crucial for any software development life cycle. While traditional code generation can fall short in identifying the target goals effectively, automated code generation can be a game-changer. This is because AI tools typically generate snippets of reusable codes and write code lines as instructed. As a result, they save a substantial amount of money, labor, and time. Benefits of Artificial Intelligence in Software Development Incorporating artificial intelligence in software development can do wonders. Considering the incredible impact of AI on software development and the possibility of incredible transformations in the future software technologies due to AI, here are some promising benefits of AI software development. Enhanced accuracy in estimates Conceptual decision making Error-free end product Easy bugs and error detection Improved data security Conclusion The software development landscape is rapidly changing, and AI has a lot to do with it. Being an enterprise, you need to understand the benefits of AI and how it is enriching human lives worldwide. It's hard to deny the tremendous pressure on the current software development industry from the demand for applications. However, it’s one of the fastest-growing industries, and AI can simplify it with secure, unique, and scalable solutions. Unquestionably, AI software development is the future, and adopting it is the best decision enterprises can make. Frequently Asked Questions What are the things to consider when adopting AI for software development? It would help if you consider the following factors to reach new heights with AI software development: Cloud is necessary for AI AI solutions are much more than implementing machine learning algorithm AI is near real-time or real-time Big data is required for AI Machine learning-powered AI solitons may need frequent retraining What are the real-world examples of integrating AI into software development? Here are some examples of AI tools that several organizations are using for efficient AI software development: Deep Code Stack Overflow AutoComplete Google Bugspot Tool w3C What are the top machine learning and AI tools software developers should consider? Generally, Machine learning software, Deep Learning software, AI platforms, and Chatbots are the four major types of software. Apart from the tools mentioned above, developers should consider the following AI tools for the enhancement of software development: Google Cloud’s AutoML Engine Kite AIDA Testim.io IBM Watson Amazon Alexa Cortana TensorFlow Azure Machine Learning Studio { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "What are the things to consider when adopting AI for software development?", "acceptedAnswer": { "@type": "Answer", "text": "It would help if you consider the following factors to reach new heights with AI software development: Cloud is necessary for AI AI solutions are much more than implementing machine learning algorithm AI is near real-time or real-time Big data is required for AI Machine learning-powered AI solitons may need frequent retraining" } },{ "@type": "Question", "name": "What are the real-world examples of integrating AI into software development?", "acceptedAnswer": { "@type": "Answer", "text": "Here are some examples of AI tools that several organizations are using for efficient AI software development: Deep Code Stack Overflow AutoComplete Google Bugspot Tool w3C" } },{ "@type": "Question", "name": "What are the top machine learning and AI tools software developers should consider?", "acceptedAnswer": { "@type": "Answer", "text": "Generally, Machine learning software, Deep Learning software, AI platforms, and Chatbots are the four major types of software. Apart from the tools mentioned above, developers should consider the following AI tools for the enhancement of software development: Google Cloud’s AutoML Engine Kite AIDA Testim.io IBM Watson Amazon Alexa Cortana TensorFlow Azure Machine Learning Studio" } }] }

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AI TECH

Build The Truth Block By Block

Article | June 8, 2021

There is nothing new about fake news. It has been in existence for centuries, albeit without the scaffolding of support from social media. From housewives’ tales to gossip magazines, the Trojan horse to the misinformation around the D-Day landing site, fake news has been a rite of passage. The Russian military made this into a fine art with “maskirovka,” the doctrine gaining superiority through deception, denial and disinformation. However, it was the 2016 U.S. presidential election that branded it with a legit identity and with such alacrity that today, I find myself questioning everything I read or hear about, no matter the veracity of the source. Fake news is a contagion that has the potency to be as disruptive as the coronavirus and must be fought with equal urgency. If you cannot solve the problem, manage it. The power behind fake news is big data — the quantum of data generated and its velocity of distribution. Big data feeds companies with interesting consumer insights on evolving trends and behaviors, which are then beautifully packaged into text, video or audio content by harnessing machine learning and deep learning algorithms. The slips happen here. If I were to personify fake news, Cersei Lannister, the manipulative, power-hungry queen in Game of Thrones, would be the perfect candidate. Cersei embellishes the truth with dramatic twists and turns to create compelling lies. We experienced a similar situation when news broke that President Trump’s grandfather owned the Arctic Restaurant and Hotel in Bennett, British Columbia, during the 1890s and 1900s, which fueled an interesting twist on the source of the family's wealth. While AI will help us identify fake news, we need a preventive measure that nips it in the bud It is almost difficult to differentiate fake news from real news. While AI will help us identify fake news, we need a preventive measure that nips it in the bud — a vaccination rather than medication. If tech helps in creating an issue, should tech help solve it too? Based on my years of experience in implementing these solutions for large enterprises and developing next-gen blockchain offerings with startups, I believe blockchain may just be the remedy we are looking for. Most technologists, however, do not consider blockchain to be a relevant or credible technology, with the primary criticisms being its lack of widespread adoption and its esotericism. But I believe the contrary. The vision of grandma-proof blockchain is becoming real — to create an inclusive global, scalable blockchain solution that can cater to every human need. Blockchain should be our weapon to effectively reduce and ultimately eradicate fake news. In blockchain, no single individual or group holds the authority, but everyone needs to approve; therefore, it enables the highest degree of integrity, privacy and security Blockchain is nothing but a distributed ledger that helps build trust in decentralized networks and that runs on the computing power of its participants. No single individual or group holds the authority, but everyone needs to approve; therefore, it enables the highest degree of integrity, privacy and security. This is accomplished by consensus algorithms. Each blockchain has adopted some form of it, and some even claim to have consensus that can prevent obfuscation of the truth even when faced with over 90% malicious intent. Blockchain technology enables a "shared single version of truth" across multiple entities based on two fundamental characteristics: immutability and traceability. Immutability Immutability is when a blockchain ledger has the capability to remain unaltered, effectively ensuring that any data on the blockchain cannot be altered — only built upon. Each block created has a unique identity and timestamp attached to it that builds a fortress around the data. Innovative upcoming blockchains use crypto-biometric identity to further buttress the fort. For example, Mediachain, a decentralized independent music library, uses blockchain to protect the originator’s authenticity by providing information about the creator, producer and lyrics to listeners. Steemit is a decentralized social media site that rewards content creators who also interact with other users. Each content piece or interaction is recorded on the immutable record by blockchain. And if news companies were to adopt blockchain — and organizations like the New York Times are already working on this — this is what we might expect: Journalists could create a block (an entry in a distributed ledger) and upload news via text, image or video. Editors would then create another new block with an edited version of the news, leaving the original block unchanged. Publishers (news agencies) would then publish the news based on their block and any changes that they might make. Each one of the participants is authenticated on the blockchain with a simple touch of their finger while protecting the fidelity of the news. Remember, entries cannot be changed, only built upon, and therefore, each change is recorded and allocated to a specific entity. For someone to “fake” the news, they would have to alter the data at each level. Infiltrating the high-security protocols would require considerable time and resource allocations. Traceability As mentioned, each block that is created has a distinct identity attached, preferably a crypto-biometric for added security and individual control. So, if fake news is generated and circulated through social media using blockchain as the base, it becomes easier to pinpoint the culprit while establishing the real source of the news. This would ascribe true content ownership to credible creators. Fake news creators are using advanced tech stacks to create deepfakes for digital deception. Generative adversarial networks (GANs) can help them to create deepfakes of images and videos that can even counteract or deceive advanced AI/ML algorithms. Of course, GANs are also being used to detect fake news now. If technology has helped fake news become compelling and believable, let’s use intelligent and available technology like blockchain to at least control it, if not eradicate it. Then again, if blockchain had existed in the medieval ages, we would have been denied the entertaining antics of Cersei Lannister and the wonderful blockbuster series that kept most of us enthralled!

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FirstAlign enables you, your team, and your organization to lead with targeted tools supported by a creative, seasoned group of professionals, from diverse disciplines and the Artificial Intelligence space. We work across major industry sectors, public companies, fortune 2000 and government authorities, utilizing startup mindsets in making complexity simple.

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