Mediaboss Marketing

Project Veritas Action Fund (PVA) Appeared in the United States First Circuit Court of Appeals for the First Circuit to Challenge the Nations Broadest Recording LawSection 99 of Massachusetts Law. PVA Argued that Undercover Recordings are at the core of citizens First Amendment Rights.Massachusetts is the Only State in the Country to Outright Ban All Secret Audio Recordings.Eleven States have Found Ways to Respect Both the First Amendment and Privacy Concerns; PVA Expects the Same from the Massachusetts Legislature.The ACLUs Sister Lawsuit was Also the Subject of the District Court Judges Decree and Appeared in Court with PVA, Focusing its Arguments Solely in Favor of Secretly Recording Police Officers.

Copy and paste this HTML code into your webpage to embed.

(Boston, MA) Project Veritas Action Fund appeared in the US First Circuit Court of Appeals for the First Circuit yesterday to challenge Section 99 of Massachusetts law. This is a law that broadly restricts any sort of undercover recording.

PVA argues that, as a result of this law, the American public will miss out on newsworthy information derived from such recordings. Further, PVA states that Section 99 infringes on citizens First Amendment rights.

There are eleven states that believe it is the legislatures responsibility to provide some level of privacy protection in conversations, but Massachusetts is the only state to fully apply privacy protections without consideration for the citizens right to secretly record. PVA argued that Massachusetts, like those eleven states, should narrow its law.

PVA has asked the court to strike down the Section 99 law facially, that is to declare it entirely void. PVA wants the court to allow the Massachusetts legislature a chance to go back to the drafting table and write a new law that complies with the First Amendment.

According to PVAs attorney Ben Barrs observation of the oral argument, it appeared that all of the judges (including former US Supreme Court Associate Justice, David Souter) expressed real skepticism about the Constitutionality of the Massachusetts lawreferring to it as sweeping too broadly in several of their questions.

Ben Barr also observed that the specific line of questioning examines the states interest in securing privacy against the means the state employs to secure that privacy. In this case, an outright ban is simply too suppressive of speech and narrower tools could be used to protect truly private conversations.

In addition, the judges hinted that individuals were free to guard their own privacysuch as removing a discussion to a truly private placeinstead of needing a law that simply prohibits newsgathering of items disclosed in public.

Here are a few of the exchanges between PVA Attorney Ben Barr, Judge Barron, and Judge Selya:

Ben Barr: Massachusetts makes a mockery of the most effective form of newsgathering, undercover journalism, by denying citizens the right to be able to go out into public, and to be able to gather information in the most effective way possible, that is, secret audio recording.

Judge Barron: What do you mean by public?

Ben Barr: I mean a place in particular where there is no reasonable expectation of privacy. It brings me to the truly exceptional nature of Section 99.

Judge Barron: Just so I get it straight with the idea that everybody in this courtroom right now would have a First Amendment right to record these proceedings?

Ben Barr: Yes.

Judge Barron: Thats your position?

Ben Barr: Yes.

Judge Barron: Do you have a narrower position?

[laughter among those present]..

Judge Selya: Commonwealth has an interest in protecting the privacy of conversations. Everyone has some sort of right to the privacy of their conversations, full stop. And you can disagree with that as a matter of policy, but youve got to figure out why thats wrong as a matter of Constitutional law

Ben Barr: Primarily, it amounts to the tailoring and overbreadth issue, Judge Selya, while there is a legitimate governmental interest in protecting conversational privacy and 11 states have worked out test to do that. On the other end of the Constitutional equation is a right to be able to acquire information in public and report on that to the American people. So, being able to record a bribe occurring with a police officer on a

Judge Selya: But Massachusetts is talking not only about governmental privacy, theyre talking about the privacy of all participants in these conversations, which typically take place between a government official and a private citizen.

Ben Barr: Yes, and actually as was noted by Judge Barron earlier, it is entirely capable that government officials and individuals are able to safeguard their own privacy. If they have a confidential conversation, or an informant, theyre able meet in a private place. We are not alleging the right to be able to invade doctors offices or police stations

Judge Barron: Yeah, but you are saying that if I think that Ive taken precautions, that I sometimes might sit on a bench in the park and speak in what I think is in pretty confidential tones with someone else, and youre saying but Im at risk of someone having a recording device, and if I didnt notice it, that can then be sent all over the place, right?

Judge Selya: I want you to note that even in his hypotheticals, Judge Barron sees himself sitting on a bench.

(Laughter)

Judge Selya also addressed Massachusetts Assistant Attorney General, Eric Haskell:

Judge Selya to MA Assistant Attorney General Eric Haskell: Meeting with a confidential informant, if its done in public, whats wrong with that being recorded? If the police officer wants that meeting to be truly confidential, the police officer can control where the meeting is held. Easy enough to hold it in private.

Judge Selya to MA Assistant Attorney General Eric Haskell: Youre saying that if John Doe comes along, sees a police officer conversing with a politician, for example, they both have their backs turned to him, he holds out, in plain view of everybody, a tape recorder and turns it on, or a cell phone, and turns on the recording function, alright? They have their backs turned, but its in plain view to anyone who wants to walk. Everyone in the Boston Common sees it, except maybe the two people who were talking, and youre saying that is, or isnt, a violation of the statute?

The ACLU had a more limited vision of how to tackle the Massachusetts recording law.

Representing the ACLU was Jessie Rossman, who said that They focus exclusively on police officers, who, unlike other officials, are armed by the state and have the authority to take people into custody.

After the hearing, Ben Barr said:

We were pleased that the court held the Commonwealth of Massachusetts to accountability. This law is an outright ban on the most effective form of newsgatheringundercover journalismand deprives the public of important information. It is difficult to imagine it surviving todays review before the First Circuit.

If the First Amendment means anything, it means that citizens possess the power to hold accountable those in power. In 2020, using smartphones and digital recording devices to uncover political hypocrisy and self-dealing is the most effective means to do so and should be protected by the First Amendment.

Project Veritas Action Fund will never cease fighting for Americans Constitutional rights. It is imperative that individual citizens are allowed to perform their FirstAmendment right to report on public and private corruption. For many citizen journalists, undercover recording is the most effective way of delivering newsworthy facts to the public.

Originally posted here:
Project Veritas Action Fund Defends Citizens' First Amendment Rights for Undercover Secret Recording in First Circuit Court of Appeals - Project...

Many people recoil at the notion that the First Amendment protects the speech that they most dislike or detest.

The late great Nat Hentoff captured this censorial impulse in his Free Speech for Me, But Not for Thee.

But the reality is that the First Amendment protects much speech that is obnoxious, offensive and repugnant.

Justice William Brennan captured this principle eloquently in his majority opinion in the flag-burning decision Texas v. Johnson (1989):

If there is a bedrock principle underlying the First Amendment, it is that the government may not prohibit the expression of an idea simply because society finds the idea itself offensive or disagreeable.

The case involved the protest activities of Gregory Lee Johnson, who burned an American flag in 1984 in Dallas, the site of the Republican National Convention. While Johnson doused the flag with kerosene, others chanted, America, red, white and blue, we spit on you.

Johnson and others protested the policies of the Reagan administration and a coming second term for the president.

Of all the protesters, authorities arrested only Johnson and charged him with violating a Texas flag desecration law.

The court decided the case by the narrowest of margins, 5-4. Brennan emphasized that the state of Texas essentially was punishing Johnson for his dissident political views more than tarnishing a venerated object.

The way to preserve the flags special role is not to punish those who feel differently about these matters, Brennan wrote. It is to persuade them they are wrong.

In dissent, Chief Justice William Rehnquist analogized Johnsons burning of the flag to fighting words. But, in this case, Brennans view prevailed.

A lasting legacy of Brennans opinion in Texas v. Johnson is his bedrock principle phrase, which has come to represent a cardinal principle of First Amendment law that the First Amendment protects much offensive expression.

David L. Hudson Jr. is a First Amendment Fellow at the Freedom Forum Institute and a law professor at Belmont University.

Read the original:
David L. Hudson Jr. | The 'bedrock principle' of the First Amendment - TribDem.com

Posted: Jan 9, 2020 / 02:24 PM EST / Updated: Jan 9, 2020 / 02:24 PM EST

WASHINGTON, D.C. (RTDNF) TheRadio Television Digital News Foundationhas announced the winners of the30thannual First Amendment Awards. The distinguished group of honorees represent the valuable role journalists play in local and national media to practice the First Amendment. A total of 7 awards will be given in 2020 and the honorees will join115 previous winnerswho championed a vital part of our democracy.

The 2020 honorees are:

As the RTDNF Board of Trustees discussed the candidates, there was overwhelming support for the accomplishments and the impact our 2020 honorees have made to journalism, stated RTDNF chairman and vice president of local content development for Nexstar Broadcasting Jerry Walsh. This years honorees are a mix of local and network journalists that provide illuminating reporting, a respected national news program which holds the powerful accountable and a visionary who defends the publics right to know.

Each honoree will be awarded at the First Amendment Awards Dinner & Show onMarch 5, 2020at the Marriott Marquis inWashington, DC. Sponsorships and tickets are available now atwww.firstamendmentawards.org. The event draws some 500 of the biggest names in broadcast and digital journalism. Additional information on the winners will be announced in the coming weeks.

Every day journalists and news professionals are working hard to keep the publics trust through truthful reporting, more transparency and responsible journalism that often serves as a catalyst for positive change, saidDan Shelley, executive director of RTDNA/RTDNF. These awards allow us to honor the efforts of all journalism professionals, and shine a light on those companies, individuals and political figures who publicly champion journalism and journalists as essential to democracy.

In addition to recognizing responsible journalism, the First Amendment Awards Dinner & Show is the Foundations biggest annual fundraiser, enabling the Foundation to ensure that the broadcast and digital news profession remains a critical part of our nations free press for generations to come and supporting scholarships for journalism students.

Read Steve Andrews investigations:

SOURCE Radio Television Digital News Foundation

See the original post here:
Investigator Steve Andrews honored with RTDNF Lifetime Achievement Award - WFLA

Jonathan Reisman, an associate professor of economics andpublic policy at the University of Maine at Machias, is appealing his case, Reisman v. Associated Faculties of theUniversity of Maine (AFUM), to the U.S. Supreme Court.

On Friday, Jan. 2, The Buckeye Institute, the organization representing Reisman in his case, filed an appeal to SCOTUS calling for an end to laws in Maine and other states that force public-sector employees to accept compelled union representation. This process, called exclusive representation (a policy for which unions advocate), prevents nonmember employees in a bargaining unit from representing themselves in matters with their employer.

In 2018, the high court ruled in Janus v. American Federation of State, County and Municipal Employees (AFSCME) that public employees cannot be required to pay dues or fees to a labor union as a condition of employment. Before Janus, nonmember public employees were compelled to pay agency fees to a union for the cost of the organizations representational activities concerning the employee, despite rejecting the unions representation by refusing to join or opting out of membership.

SCOTUS ruled this practice violates the First Amendment rights of public employees. Reisman is asking the high court to consider exclusive representation laws under the same principle. If compelled payments to a union violate a public employees First Amendment rights, compelled representation must also violate employees rights.

Professor Reisman is a hardworking public employee who has for many years been forced to associate with a union with which he disagrees and suffer it to speak for him,saidRobert Alt, president and chief executive officer ofThe Buckeye Instituteand a lead attorney on the case. If state law cannot compel public employees to financially support union advocacy as the court ruled inJanus v. AFSCME how can states require these same public employees to accept representation from unions that many of them have chosen not to join? These are serious questions about the constitutionality of exclusive representation questions which the U.S. Supreme Court needs to address.

Despite resigning hisunion membership, Professor Reisman is required by Maine law be represented bya union with which he does not agree and of which he is not amember,saidAndrew M. Grossman, a partner at BakerHostetler in Washington,D.C., and counsel of record on theReisman v. AFUMpetition.Following the Courts landmarkJanusruling, it is clearthat these laws are unconstitutional, and we hope the Court will recognize themas such.

Reisman formerly served as a grievance officer with hisunion before resigning his membership after the Janus decision. His former union, AFUM, is affiliated with theMaine Education Association and the National Education Association, which hastaken political stances that Reisman finds objectionable.

While the outcome of Janus freed him from the requirement ofeither joining the union or being forced to pay representation fees, Maine lawstill forces AFUM to be Reismans exclusive representative, meaning he is stillassociated with the positions the union takes.

If the Supreme Court agrees to hear Reismans case and rules in his favor, the First Amendment rights of public employees to represent themselves in matters with their employer would be restored. The end result is true freedom of speech and association, not compelled speech and association as required by state labor law.

The Buckeye Institute is also representing public employees in other post-Janus lawsuits throughout the country, including Kathy Uradnik of St. Cloud State University in Uradnik v. Inter Faculty Organization and Jade Thompson, a Spanish teacher in Ohio, in Thompson v. Marietta Education Association.

Visit link:
Maine professor suing faculty union appeals his case to the Supreme Court - The Maine Wire

From Machine Learning to Machine Reasoning

The conversation around Artificial Intelligence usually revolves around technology-focused topics: machine learning, conversational interfaces, autonomous agents, and other aspects of data science, math, and implementation. However, the history and evolution of AI is more than just a technology story. The story of AI is also inextricably linked with waves of innovation and research breakthroughs that run headfirst into economic and technology roadblocks. There seems to be a continuous pattern of discovery, innovation, interest, investment, cautious optimism, boundless enthusiasm, realization of limitations, technological roadblocks, withdrawal of interest, and retreat of AI research back to academic settings. These waves of advance and retreat seem to be as consistent as the back and forth of sea waves on the shore.

This pattern of interest, investment, hype, then decline, and rinse-and-repeat is particularly vexing to technologists and investors because it doesn't follow the usual technology adoption lifecycle. Popularized by Geoffrey Moore in his book "Crossing the Chasm", technology adoption usually follows a well-defined path. Technology is developed and finds early interest by innovators, and then early adopters, and if the technology can make the leap across the "chasm", it gets adopted by the early majority market and then it's off to the races with demand by the late majority and finally technology laggards. If the technology can't cross the chasm, then it ends up in the dustbin of history. However, what makes AI distinct is that it doesn't fit the technology adoption lifecycle pattern.

But AI isn't a discrete technology. Rather it's a series of technologies, concepts, and approaches all aligning towards the quest for the intelligent machine. This quest inspires academicians and researchers to come up with theories of how the brain and intelligence works, and their concepts of how to mimic these aspects with technology. AI is a generator of technologies, which individually go through the technology lifecycle. Investors aren't investing in "AI, but rather they're investing in the output of AI research and technologies that can help achieve the goals of AI. As researchers discover new insights that help them surmount previous challenges, or as technology infrastructure finally catches up with concepts that were previously infeasible, then new technology implementations are spawned and the cycle of investment renews.

The Need for Understanding

It's clear that intelligence is like an onion (or a parfait) many layers. Once we understand one layer, we find that it only explains a limited amount of what intelligence is about. We discover there's another layer thats not quite understood, and back to our research institutions we go to figure out how it works. In Cognilyticas exploration of the intelligence of voice assistants, the benchmark aims to tease at one of those next layers: understanding. That is, knowing what something is recognizing an image among a category of trained concepts, converting audio waveforms into words, identifying patterns among a collection of data, or even playing games at advanced levels, is different from actually understanding what those things are. This lack of understanding is why users get hilarious responses from voice assistant questions, and is also why we can't truly get autonomous machine capabilities in a wide range of situations. Without understanding, there's no common sense. Without common sense and understanding, machine learning is just a bunch of learned patterns that can't adapt to the constantly evolving changes of the real world.

One of the visual concepts thats helpful to understand these layers of increasing value is the "DIKUW Pyramid":

DIKUW Pyramid

While the Wikipedia entry above conveniently skips the Understanding step in their entry, we believe that understanding is the next logical threshold of AI capability. And like all previous layers of this AI onion, tackling this layer will require new research breakthroughs, dramatic increases in compute capabilities, and volumes of data. What? Don't we have almost limitless data and boundless computing power? Not quite. Read on.

The Quest for Common Sense: Machine Reasoning

Early in the development of artificial intelligence, researchers realized that for machines to successfully navigate the real world, they would have to gain an understanding of how the world works and how various different things are related to each other. In 1984, the world's longest-lived AI project started. The Cyc project is focused on generating a comprehensive "ontology" and knowledge base of common sense, basic concepts and "rules of thumb" about how the world works. The Cyc ontology uses a knowledge graph to structure how different concepts are related to each other, and an inference engine that allows systems to reason about facts.

The main idea behind Cyc and other understanding-building knowledge encodings is the realization that systems can't be truly intelligent if they don't understand what the underlying things they are recognizing or classifying are. This means we have to dig deeper than machine learning for intelligence. We need to peel this onion one level deeper, scoop out another tasty parfait layer. We need more than machine learning - we need machine reasoning.

Machine reason is the concept of giving machines the power to make connections between facts, observations, and all the magical things that we can train machines to do with machine learning. Machine learning has enabled a wide range of capabilities and functionality and opened up a world of possibility that was not possible without the ability to train machines to identify and recognize patterns in data. However, this power is crippled by the fact that these systems are not really able to functionally use that information for higher ends, or apply learning from one domain to another without human involvement. Even transfer learning is limited in application.

Indeed, we're rapidly facing the reality that we're going to soon hit the wall on the current edge of capabilities with machine learning-focused AI. To get to that next level we need to break through this wall and shift from machine learning-centric AI to machine reasoning-centric AI. However, that's going to require some breakthroughs in research that we haven't realized yet.

The fact that the Cyc project has the distinction as being the longest-lived AI project is a bit of a back-handed compliment. The Cyc project is long lived because after all these decades the quest for common sense knowledge is proving elusive. Codifying commonsense into a machine-processable form is a tremendous challenge. Not only do you need to encode the entities themselves in a way that a machine knows what you're talking about but also all the inter-relationships between those entities. There are millions, if not billions, of "things" that a machine needs to know. Some of these things are tangible like "rain" but others are intangible such as "thirst". The work of encoding these relationships is being partially automated, but still requires humans to verify the accuracy of the connections... because after all, if machines could do this we would have solved the machine recognition challenge. It's a bit of a chicken and egg problem this way. You can't solve machine recognition without having some way to codify the relationships between information. But you can't scalable codify all the relationships that machines would need to know without some form of automation.

Are we still limited by data and compute power?

Machine learning has proven to be very data-hungry and compute-intensive. Over the past decade, many iterative enhancements have lessened compute load and helped to make data use more efficient. GPUs, TPUs, and emerging FPGAs are helping to provide the raw compute horsepower needed. Yet, despite these advancements, complicated machine learning models with lots of dimensions and parameters still require intense amounts of compute and data. Machine reasoning is easily one order or more of complexity beyond machine learning. Accomplishing the task of reasoning out the complicated relationships between things and truly understanding these things might be beyond today's compute and data resources.

The current wave of interest and investment in AI doesn't show any signs of slowing or stopping any time soon, but it's inevitable it will slow at some point for one simple reason: we still don't understand intelligence and how it works. Despite the amazing work of researchers and technologists, we're still guessing in the dark about the mysterious nature of cognition, intelligence, and consciousness. At some point we will be faced with the limitations of our assumptions and implementations and we'll work to peel the onion one more layer and tackle the next set of challenges. Machine reasoning is quickly approaching as the next challenge we must surmount on the quest for artificial intelligence. If we can apply our research and investment talent to tackling this next layer, we can keep the momentum going with AI research and investment. If not, the pattern of AI will repeat itself, and the current wave will crest. It might not be now or even within the next few years, but the ebb and flow of AI is as inevitable as the waves upon the shore.

See the original post:
Going Beyond Machine Learning To Machine Reasoning - Forbes