The US presidential election is in its final stretch. Before election day on November 5, Engadget is looking at where the candidates, Kamala Harris and Donald Trump, stand on the most consequential tech issues of our day. While it might not garner the headlines that immigration, abortion or inflation do, AI is quietly one of the more consequential issues this election season. What regulations are put in place and how forcefully those rules are enforced will have wide ranging impacts on consumer privacy, intellectual property, the media industry and national security. Normally, politicians lack clear or coherent policies on emerging technologies.

The adoption of artificial intelligence (AI) in retail has significantly transformed the industry, enabling more personalized services and efficient operations. However, the rapid implementation of AI technologies raises ethical concerns, particularly regarding consumer privacy and fairness. This study aims to analyze the ethical challenges of AI applications in retail, explore ways retailers can implement AI technologies ethically while remaining competitive, and provide recommendations on ethical AI practices. A descriptive survey design was used to collect data from 300 respondents across major e-commerce platforms. Data were analyzed using descriptive statistics, including percentages and mean scores. Findings shows a high level of concerns among consumers regarding the amount of personal data collected by AI-driven retail applications, with many expressing a lack of trust in how their data is managed. Also, fairness is another major issue, as a majority believe AI systems do not treat consumers equally, raising concerns about algorithmic bias. It was also found that AI can enhance business competitiveness and efficiency without compromising ethical principles, such as data privacy and fairness. Data privacy and transparency were highlighted as critical areas where retailers need to focus their efforts, indicating a strong demand for stricter data protection protocols and ongoing scrutiny of AI systems. The study concludes that retailers must prioritize transparency, fairness, and data protection when deploying AI systems. The study recommends ensuring transparency in AI processes, conducting regular audits to address biases, incorporating consumer feedback in AI development, and emphasizing consumer data privacy.

Web 3.0 promises a fundamental change to the internet, strongly emphasizing consumer privacy -- an issue that has been thrown around for a while but not adequately addressed. Whereas Web 2.0 featured the internet as a platform for building applications, Web 3.0 features the internet on blockchain technology. Storing consumer data on blockchain decentralizes that data, and makes data use by companies transparent, reportedly protecting it from breaches. Returning data ownership back to consumers can potentially disrupt the tech industry since many tech giants would presumably lose access to the data that gave them a leg up on the competition. Blockchain is only one of the highly advanced technologies that will contribute to this evolution.

Researchers from University of Minnesota, New York University, University of Pennsylvania, BI Norwegian Business School, University of Michigan, National Bureau of Economic Research, and University of North Carolina published a new paper in the Journal of Marketing that examines how advances in machine learning (ML) and blockchain can address inherent frictions in omnichannel marketing and raises many questions for practice and research. The study, forthcoming in the Journal of Marketing, is titled "Informational Challenges in Omnichannel Marketing Remedies and Future Research" and is authored by Koen Pauwels, Haitao (Tony) Cui, Catherine Tucker, Raghu Iyengar, S. Sriram, Anindya Ghose, Sriraman Venkataraman, and Hanna Halaburda. In this new study in the Journal of Marketing, researchers define omnichannel marketing as the "synergistic management of all customer touch points and channels both internal and external to the firm that ensures that the customer experience across channels and firm-side marketing activity, including marketing-mix and marketing communication (owned, paid, and earned), is optimized." Often viewed as the panacea for one-to-one marketing, omnichannel experiences data, marketing attribution, and consumer privacy frictions. The research team demonstrates that advances in machine learning (ML) and blockchain can address these frictions.

Consumer privacy has made big headlines in the recent years with the Facebook Cambridge Analytica Scandal, Europe's GDPR and high-profile breaches by companies like Equifax. It's clear that the data of millions of consumers is at risk every day, and that companies that wish to handle their data must do so with the highest degree of protection around both security and privacy of that data, especially for companies that build and sell AI-enabled facial recognition solutions. As CEO of an AI-enabled software company specializing in facial recognition solutions, I've made data security and privacy among my top priorities. Our pro-privacy stance goes beyond mere privacy by design engineering methodology. We regularly provide our customers with education and best practices, and we have even reached out to US lawmakers, lobbying for sensible pro-privacy regulations governing the technology we sell.

Conversational user experiences, in the form of chatbots and voice interfaces, are overtaking many of the traditional ways in which we interact with machines. Since the rise of computers, human-machine interfaces typically had some form of Graphical User Interface (GUI) which enabled direct (if limited) interaction with devices and their programs, for instance via software installs, mobile apps, and web-based applications such as Software as a Service (SaaS). No matter how "beautiful" the respective interface, this GUI is now more and more replaced by a Conversational User Interface (CUI). Other still evolving interface styles are less text- and voice-driven, and therefore limit the messaging element to certain basic functions such as taking photos with the blink of an eye (smart glasses or smart cameras such as Blincam can do that today) but will eventually allow for richer interaction gestures (see project Soli). When coupled with an input-output feedback loop, so-called bionic lenses also hold a promising future.

Something very interesting is happening within the tech world: the biggest tech giants in Silicon Valley are racing to make your home a vast new playground for all of their new tech devices and platforms. But whatever you do – don't call it the "smart home." According to Google executives, the term "smart home" has fallen out of favor at the company, presumably because it conjures up all kinds of images of surveillance cameras and smart home devices that are constantly monitoring, tracking and listening to you. A better term, according to top Google executives, is the "helpful home." A "helpful home" respects consumer privacy and comes with all sorts of features and benefits to make your life easier.